Clarias Gariepinus

AQUATIC RESEARCH E-ISSN 2618-6365

Chief Editor: Prof.Dr. Nuray ERKAN, Turkey Prof.Dr. Tamuka NHIWATIWA, Zimbabwe [email protected] [email protected] Subjects: Processing Technology, Food Sciences and Engineering Subjects: Fisheries Institution: Istanbul University, Faculty of Aquatic Sciences Institution: University of Zimbabwe, Department of Biological Sciences

Cover Photo: Prof.Dr. Özkan ÖZDEN, Turkey [email protected] Ferhan Çoşkun, Turkey Subjects: Fisheries, Food Sciences and Engineering Phone: +90 532 763 2230 Institution: Istanbul University, Faculty of Aquatic Sciences [email protected] İnstagram: instagram.com/exultsoul Prof.Dr. Murat YİĞİT, Turkey [email protected] Subjects: Fisheries Institution: Canakkale Onsekiz Mart University, Faculty of Marine Editorial Board: Science and Technology

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AQUATIC RESEARCH E-ISSN 2618-6365

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II AQUATIC RESEARCH E-ISSN 2618-6365

Vol. 4 Issue 1 Page 1-115 (2021)

Content/İçerik

RESEARCH ARTICLES

Stochastic frontier analysis of catfish (Clarias gariepinus) aquaculture agribusiness for sustainable fisheries development: Evidence from Nigeria / 1-9 Eguono Aramide IKPOZA, Felix Odemero ACHOJA, Oraye Dicta OGISI, Christy ULIONG

İstanbul Boğazı’ndaki ticari gemi kazalarının karar ağacı yöntemiyle analizi / 10-20 Erkan ÇAKIR, Bünyamin KAMAL

Community structure of mayflies (Insecta: Ephemeroptera) in tropical streams of Western Ghats of Southern India / 21-37 Sivaruban BARATHY, Thambiratnam SİVARUBAN, Muthukumarasamy ARUNACHALAM, Pandiarajan SRİNİVASAN

The fishes of the Bolaman Stream, Northern Turkey / 38-54 Serkan SAYGUN

COMMUNICATION

A review on maximum length of the greater weever Trachinus draco Linnaeus 1758 (Perciformes: Trachinidae) with a new maximum length from Oran Bay (Western Algeria) / 55-64 Lotfi BENSAHLA-TALET, Hichem ADDA NEGGAZ

Diagnosis of Aeromonas sobria and Saprolegnia sp. co-infection in rainbow trout fry (Oncorhynchus mykiss) / 65-72 Remziye Eda YARDIMCI, Emre TURGAY

REVIEW ARTICLES

Gıda güvenliği açısından su ürünlerinde mikroplastik riski ve araştırma yöntemleri / 73-87 İdil� CAN TUNÇELLİ, Nuray ERKAN

Chhecklist of marine diatoms from the Turkish coastal waters with updated nomenclature / 88-115 Aydın KALELİ, Reyhan AKÇAALAN

III AQUATIC RESEARCH E-ISSN 2618-6365

Aquat Res 4(1), 1-9 (2021) • https://doi.org/10.3153/AR21001 Research Article

Stochastic frontier analysis of catfish (Clarias gariepinus) aquaculture agribusiness for sustainable fisheries development: Evidence from Nigeria

Eguono Aramide IKPOZA , Felix Odemero ACHOJA , Oraye Dicta OGISI , Christy ULIONG

Cite this article as: Ikpoza, E.A., Achoja, F.O., OGISI, O.D., ULIONG, C. (2021). Stochastic frontier analysis of catfish (Clarias gariepinus) aquaculture agribusiness for sustainable fisheries development: Evidence from Nigeria. Aquatic Research, 4(1), 1-9. https://doi.org/10.3153/AR21001

Delta State University, Department of ABSTRACT Agricultural Economics and Extension, Abraka, Delta State, Nigeria Technical efficiency assessment and enhancement is critical to sustainable fisheries development in Nigeria. This study examines stochastic frontier of catfish aquaculture agribusiness for sustainable fisheries development. Purposive sampling technique was employed to select 110 catfish farmers in areas with high density catfish farms. Primary data were collected directly from catfish ORCID IDs of the author(s): farmers using structured questionnaire. The analytical tools used were descriptive statistics, net E.A.I. 0000-0002-7633-7289 farm income, stochastic frontier production function (SPF) and t-statistics. The result shows that F.O.A. 0000-0002-9705-4923 most of the catfish farmers were young people within the productive age of 40-49 years. Catfish O.D.O. 0000-0002-9068-9694 farmers had obtained various levels of formal education. Finding shows that feeds cost was the C.U. 0000-0003-4115-368X highest variable cost (72.75%). Feed had a positive and significant relationship (P<0.05) with catfish output. Mean technical efficiency is 53.49%. The estimated variance (δ2s=0.2125) is statistically significant (P<0.05), indicating that profit inefficiency is highly significant among catfish farmers. Estimated Gamma (γ) value of 0.26 implies that 26% of the total variation in catfish profit efficiency is due to the joint effect of technical inefficiency factors. The most significant efficiency Submitted: 22.05.2020 factors are fish feed and pond size. The age and educational status of farmers are the most im- Revision requested: 21.06.2020 portant determining factors of inefficiency in catfish production system. Lack of finance was the Last revision received: 07.07.2020 most serious constraint faced by catfish farmers. The study recommended that catfish farmers Accepted: 10.07.2020 should form cooperative unions to facilitate their access to cooperative funding. Published online: 25.09.2020 Keywords: Stochastic frontier analysis, Catfish aquaculture, Technical efficiency, Sustainable fisheries development

Correspondence:

Felix Odemero ACHOJA E-mail: [email protected]

Available online at http://aquatres.scientificwebjournals.com

Aquat Res 4(1), 1-9 (2021) • https://doi.org/10.3153/AR21001 Research Article

Introduction The increasing cases of global undernourishment and starva- field. However, most of the past studies in Nigeria focused on tion among human population, particularly in the developing large scale fish farming (Obasi, 2002). countries had been reported at various development debate The catfish aquaculture sector is yet to record sustainable de- fora. This is a world-wide issue of major concern that calls velopment in terms of fish output to further close demand- for scaling up of food production. There aquaculture and fish- supply gap that is evident in the sector in Nigeria (Olujimi, eries are two of the three important sources (agriculture, aq- 2002). Squires et al. (2003) and Achoja et al. (2020), reported uaculture and fisheries) of food production. As it stands, that fishers’ age and educational attainment have considera- world’s natural stock of fish has finite supply limits. Most of ble impacts on the technical efficiency fish aquaculture. natural water bodies have attained maximum fishing limit. Young and educated fishers have potential for sustainable de- Aquaculture holds the potential for sustainable aggregate fish velopment of catfish aquaculture on the basis of their youth- supply to satisfy fish increasing global fish demand (Okechi, fulness and technical skills (Revilla-Molina et al. 2009; Oy- 2004). inbo et al. 2016; Achoja et al. 2020). Aquaculture refers to the cultivation of aquatic organisms un- New technologies from research and development initiatives der controlled or semi-controlled conditions for economic generate sustainable development if they are made available and social benefits (Fourier, 2006). Catfish farming is a sub- by extension officers to catfish producers for efficient appli- set of aquaculture which involves the rearing of catfish under cation. As it stands, the relatively high inefficiencies in the controlled conditions for economic and social benefits. Ac- catfish aquaculture can be eroded with sustainable fisheries cording to Adewunmi and Olaleye (2011), the favoured cat- development policies (Baruwa and Omodara, 2019). fish for culture include Clarias gariepinus, Heterobranchus bidorsalis, Clarias heterobranchus hybrid (heteroclarias), There is dearth of empirical information on technical effi- with C. gariepinus and H. bidorsalis being the most cultured ciency of catfish aquaculture agribusiness in Nigeria. Catfish fish in Nigeria. Clarias gariepinus is regarded as an excellent business in Nigeria has low and sub-optimal technical effi- aquaculture species because it grows fast and feeds on a va- ciency. This low efficiency is attributable to the poor man- riety of agricultural by-products. It is hardy and can tolerate agement of some factors of production (Goksel 2008; Onoja extreme temperature, easy to produce in captivity with high and Achike 2011; Oyinbo et al. 2016; Baruwa and Omodara, annual production and good feed conversion rate. Globally, 2019). fish provides about 3 billion people with almost 20percent of Stochastic frontier analysis of catfish (Clarias gariepinus) their intake of animal protein, and 4.3 billion people with aquaculture agribusiness for sustainable fisheries develop- about 15 percent of such protein (FAO, 2012). Increasing de- ment is a research puzzle that is worthy of investigation. The mand for fish products has resulted in the growth of fish farms broad objective of the study is to determine the technical ef- to meet a substantial part of the world’s food requirement ficiencies of catfish aquaculture using stochastic frontier ap- (Olasukanmi, 2012). proach. The current shortfall in fish supply compared to local demand The specific objectives are to: is putting pressure on the price of fish and its products. This can make fish unaffordable for many households in Nigeria 1. Determine the socioeconomic characteristics of cat- and further decreasing the per capita fish consumption rate fish producers in the study area; (FAO, 2010). However, there is significant interest in sustain- 2. Estimate the cost and return of catfish production; able development of the catfish industry in Nigeria. A sure means of substantially solving the demand-supply gap is by 3. Estimate the technical efficiencies of catfish produc- embarking on widespread homestead/ small scale fish pro- tion; duction. Also, considerable efforts have been directed at ex- 4. Identify the production constraints faced by catfish amining productive efficiency of fish farmers in Nigeria that aquaculture farmers in the study area. is exclusively focused on technical efficiency of fish farmers in general and profitability of fish farming (Kudi et al., 2008). Material and Methods Consequent upon the increment in awareness of catfish farm- The study was conducted in Delta State, Nigeria. Delta State ing and a substantial percentage of small scale catfish farmers is located in the Niger delta Zone of Nigeria. It lies between in Nigeria, it has prompted the interest of researchers in this latitude 50001 and 60451. The state is located in the Niger Delta Region of Nigeria and lies within mangrove swamp,

Aquat Res 4(1), 1-9 (2021) • https://doi.org/10.3153/AR21001 Research Article

fresh water swamp forest and derived savannah vegetation Yi = f(X:β) + e ………………….(2) belts. The state is well irrigated naturally by many rivers, riv- ei = Vi – Ui ……………………...…(3) ulets and streams. It has two prominent seasons, the wet season which, last from March to October and the dry season Where Yi=Output of the ith farm which last from November to February. The state is shared Xi=Vector of inputs used by the ith farm into three agricultural zones The major occupation of the peo- B=Vector of the parameters estimated ple is farming and fishing. Their cropping systems are mainly mixed cropping, intercropping as well as sole cropping and ei=Composite error term the main crops cultivated in the area are cassava, yam, okra, Vi=Random error outside farmers control garden egg, cocoyam, rice maize and sweet potato. Ui=technical inefficiency effects Purposive sampling technique was used to sample 110 catfish The empirical Stochastic frontier model that will be em- farmers selected from areas with high density catfish farms. ployed is specified as follows: Data were collected from primary sources. Primary data were collected using structured questionnaire which was adminis- ln Y1 = β0 + β1lnX1i +β2lnX2i + β3lnX3i + β4lnX4i + β5lnX5i tered on the respondents. Data collected was on the socioec- + β6lnX6i +Vi – Ui………(4) onomic characteristics such as age, gender, household size, Subscripts ij refer to the jth observation of ith farmer farm size, farming experience, income and level of education ln= Logarithm to base e and data on catfish production like cost and returns, con- Y=Output of catfish(kg) straints to catfish production, income and expenditure of the household was also collected. The analytical tools that were β0=Constant employed to achieve the objectives and hypothesis of the β1 -β6=Parameters estimated study include descriptive statistics, net farm income, stochas- X1= Number of Fingerlings tic frontier production function analysis, food insecurity line X2= Fish feed (kg) and Z-statistic. Descriptive statistics such as frequency distribution, mean, percentage, minimum and maximum values X3=Labour (Man-days) was also used to achieve objectives I, and vi of the study. X4=Drugs($) Budgeting technique was used to achieve objective ii. The in- X5=Fuel (Litres) 2 dicators that were used include Net Farm Income (NFI) and X6=Pond size (m ) profitability index. NFI is expressed as: Vi=Random noise (white noise)

NFI = ΣPYiYi-ΣPXj -ΣFK……………………….(1) Ui=Inefficiency effects which are non-negative with half nor- Where: mal distribution. NFI= Net Farm Income ($)/production cycle; It is assumed that inefficiency effects are independently dis-

PYi=Unit price of the output of Catfish ($) tributed and Uij arises by truncation (at zero) of the normal 2 distribution with mean Uij and variance δU Yi= Total output of catfish (Kg); Pxj= Unit price of variable inputs ($) Where Ui is specified as: Xj=Quantity of variable inputs (where j=1,2,3,…,n) Ui= δ0+δ1lnZ1i+δ2lnZ2i+δ3lnZ3i+δ4lnZ4i+δ5lnZ5i+δ6lnZ6i

Fk= Depreciated Cost of fixed inputs ($) (where k=1,2,3,…,n) Where: =Summation sign Ui= Inefficiency effect of catfish production δ0= Constant The stochastic frontier function used by Onu et al. (2000) as derived𝚺𝚺 from the error model of Aigner et al. (1977) was em- δ1 - δ6 = Parameters to be estimated ployed to achieve objectives iii and iv. The Cobb-Douglas Z1 = Farmers age (years) production function was fitted to the frontier model of catfish Z2= Household size of farmer (number) production. The result was estimated using the maximum Z3= Years of Formal education of the farmer (years) likelihood method. The stochastic frontier production function is written as: Z4= Years of farming experience of the farmer in catfish production (years)

Z5= Number of years in cooperative society (years)

Aquat Res 4(1), 1-9 (2021) • https://doi.org/10.3153/AR21001 Research Article

Z6= Number of contacts with extension agents (measured that catfish farmers are in their prime and active age of pro- as number of contacts in a year) duction. They are likely to be productive in the next decade and catfish production in the country will likely increase. Ac- Results and Discussion cording to Sikiru, et al. (2009), this age bracket is a produc- This section deals with the results and discussion of findings tive age which predicts better future for catfish production. under the following sub-headings: Distribution of Socioeco- Gender nomic Characteristics of Catfish Farmers, Cost and Return of Catfish Production, Technical Efficiencies of Catfish Pro- Table 1 showed that both men and women were actively in- duction (technical efficiency factors and technical ineffi- volved in catfish production but the percentage of men were ciency factors), Production Constraints of Catfish farmers. more. Men accounted for 68.5% while female were about 31.25%. The high number of males might be attributed to Table 1. Distribution of demographic parameters of Catfish hard task carried out in catfish production process. Farmers Marital status Parameter Frequency/% Mode Age(years) Result from Table 1 showed that about 70% of the respond- 20-29 7(8.75) 43 ents were married. About 13.75% were single while 7.5% 30-39 16(20) were divorced and 8.75% were widowed. The high number 40-49 30(37.5) of married people in the business was to reduce labour cost 50-59 17(21.25) as most married persons have children that constitute the la- >60 10(12.5) bour force in catfish production. Gender Farming experience Male 55(68.75) 55 Female 25(31.25) Table 1 also shows the distribution of respondents by farming Marital Status experience. As shown in the table there was influx of new Married 56(70.00) 56 entrants into catfish production in recent times. This could be Unmarried 24(30.00) due to the ban on importation of frozen catfish product by the Educational Level federal government. This is represented by about 61.25% No formal education 0(0.00) 61 who had from 1-5 years of experience as the majority. This Primary 6(7.50) was followed by about 27.5% who had farming experience of Secondary 13(16.25) 6-10 years, 8.75% had farming experience of 11-15 years and Tertiary 61(76.25) 2.5% had farming experience of 6-10 years, 8.75% had farm- Farming Experience ing experience of 11-15 years and 2.5% had farming experi- 1 -5 years 49(61.25) 1-5 years ence of 11-15years and 2.5% had farming experience of 6-10 6 -10 years 22(27.50) years, 8.75% had farming experience of 11-15 years and 11 -15 years 7(8.75) 2.5% had farming experience of 16 years and above. Table 1 Above 16 years 2(2.50) shows that the average farming experience of the respondents Membership of cooperative was about 5 years which means that they were still new in the Non member 52(65.00) 52 business and had no experience in catfish production. This Member 28(35.00) agrees with Williams et al (2012), that the ability to manage Extension Contact fish pond efficiently depends on the years of experience and No 50(62.5) 50 this is directly related to the total productivity of the farm. Yes 30(37.5) Educational level Socioeconomic Characteristics of Catfish Farmers The result shows that 7.5% of small scale catfish farmers had Age six years of formal education and 26.3% of small scale catfish farmers had 12 years of formal education while 40% of small The frequency distribution of respondents according to socio scale catfish farmers had 10 years of formal education. With economic characteristics is shown in Table 1. The table this level of education, there is tendency of the farmers being shows that majority (37.5%) of the catfish farmers fell within able to increase the level of technology adopted and skill ac- the productive age range of 40-49years. The average age of quisition. This study agrees with the findings of Ologbon the catfish farmers was estimated to be 43years which means

Aquat Res 4(1), 1-9 (2021) • https://doi.org/10.3153/AR21001 Research Article

(2012) that found out that greater percentage of small scale 0.575. Since the rate of return is greater than one, catfish pro- catfish farmers in Ogun State had formal Education. duction is considered profitable in the study area. The business is profitable with about 57.5% profit on investment. The Membership of cooperative society study revealed that for every $1.00 invested in catfish pro- The result in Table 1 shows that 65% of the catfish farmers duction, a return of $0.57 is made. This result is consistent in the study area belong to a cooperative society while 35% with the finding of Alawode (2014) who observed that fish of the respondents do not belong to any cooperative society. farming is profitable. Therefore, the null hypothesis which states that catfish farming is not profitable is rejected and the Extension contact alternative accepted. The information in Table 1 reveals that majority of the farm- Table 2. Cost and Return of catfish production ers (62.5%) have access to extension service delivery while 37.5% of the catfish farmers in the study area indicated that Items Amount(₦) they do not have contact with extension agents. Variable cost Feeds 570 350 Cost and Return of Catfish Production Fingerlings 104 169 The information in table 2 shows the cost and return of catfish Medication 10 300 production in the study area. The average fixed cost incurred Labour 28 277 by the farmers in the study area amounted to the sum of Water 10 804 $444.44. Findings indicated that cost of feed accounted for Total variable cost 723 900 about $1,584.31 which is the greatest variable cost. This is Fixed cost followed by purchase of fingerlings and labour that accounted Pond preparation 108 000 for $289.36 and $78.55 respectively. From the enterprise Water pump 52 000 budget analysis for the catfish shown in the table, it could be Total fixed cost 160 000 observed that catfish production is a profitable venture in the Total cost 883 900 study area. The result of the survey shows a Gross Margin of Total Revenue 1 392 217 92.32percent and average net returns was calculated to be Gross margin 92.32% $1,411.9. The result also revealed that rate of return was Net farm income 508 317 Return on Investment 0.575

Technical Efficiency Level of Catfish Production System Table3. Profit Efficiency and inefficiency factors of catfish production Variables Parameters Coefficients Standard error t-value Profit factors Constant X0 0.2116 0.1169 1.810 Fingerlings X1 -0.9731 0.9782 -0.9948 Fish feed X2 0.7128 0.2192 3.252*** Labour X3 -0.1581 0.1457 -1.085 2 Pond Size (m ) X4 0.6071 0.1193 5.089*** Inefficiency Factors Constant Z0 0.7017 0.1169 6.002*** Age Z1 0.9397 0.1877 5.006*** Household size Z2 0.1434 0.0706 2.031** Years of Education Z3 -0.2184 0.0526 -3.951*** Farming experience Z4 -0.2068 0.1648 -1.255 Number of extension contacts Z5 -0.3251 0.1395 -2.330** Diagnostics statistics Total variance δ2 0.2125 0.0328 6.478*** Variance ratio Γ 0.2574 0.1409 1.827 LR Test 0.1727 Log-likelihood function 0.4053

Aquat Res 4(1), 1-9 (2021) • https://doi.org/10.3153/AR21001 Research Article

Estimated Profit Factors age is an important variable in the productivity of aquaculture in Nigeria. The result of maximum likelihood (ML) estimates of the Cobb-Douglas stochastic frontier production function for Household size small scale catfish farmers are presented in Table 3. The result shows that house size has a positive and significant Fingerlings relationship (p<0.05) with the technical inefficiency of catfish production system. This finding implies that a 1% in- The coefficient of cost of fingerlings is the a priori expected crease in household size will increase technical inefficiency negative sign. This implies that 1% increase in the cost and of catfish farms by 0.1434. A catfish farmer with large house- quantity of fingerlings stocked beyond a threshold level will hold will likely divert resources meant for the fish farm to reduce the quantity of catfish output and technical efficiency family upkeep to the detriment of the farm. of resource utilization as well as profit by 0.9731. Years of education Fish feed This variable entered the technical inefficiency model with a Feed has the a priori expected positive sign and significant negative coefficient (-0.2184) and significant (p<0.05). This (p<0.05) showing a direct relationship with output and profit finding indicates that increase in the years of education, es- efficiency. This implies that a 1% increase in of feed will in- pecially with catfish orientation will reduce the technical increase the quantity of catfish output by 0.7128. efficiency of catfish production system. This result implies Pond size that an educated catfish farmer will be able to adopt modern fish farming technologies and avoid wastage of farm re- Pond Size has the a priori expected positive sign and signifi- sources, thereby reducing technical inefficiency. This result cant (p<0.05) showing a direct and positive relationship with collaborates with the earlier report of Achoja et al. (2020) that output and profit efficiency. This implies that a 1% increase education is an important human capital variable in the in of feed will increase the quantity of catfish output by productivity of aquaculture in Nigeria. 0.6071. Number of extension contacts Technical Inefficiency Factors The frequency of extension contact with catfish farmer en- Table 3 shows the result of technical inefficiency factors in 2 tered the technical inefficiency function with a negative co- catfish production system. The estimated variance δ = efficient (-0.3251) and it is significant (p<0.05). This implies 0.2125 is statistically significant at 1% level of probability. that the more the number of extension contact a catfish farmer This value indicates that profit inefficiency is highly signifi- has with extension officers the lower the technical ineffi- cant in the catfish farmers’ production activities. The γ pa- ciency in the catfish production system. More access to ex- rameter shows the relative magnitude of the variance in out- tension information on catfish production the lower the re- put associated with technical efficiency. The coefficients of sulting technical inefficiency. the variables derived from the Maximum Likelihood Estima- tion (MLE) are very important for discussing results of the Technical Efficiency of Catfish Farms analysis of the data. This coefficient represents percentage Table 4. Analysis of Technical Efficiency of Catfish Farms change in the dependent variables due to percentage change in the independent (or explanatory) variables. The value of Technical Efficiency level (%) Frequency Percentage estimated Gamma (γ) is 0.2574 and is statistically significant <41 14 17.5 at (p<0.05) indicating that 26% of the total variation in catfish 41-50 18 22.5 profitability is due to technical inefficiency factors. 51-60 35 43.75 61-70 12 15 Age 71-80 1 1.25 Age of catfish farmers entered the technical inefficiency 81-90 0 0 model with a negative sign (-0.9397) and significant 91-100 0 0 (p<0.05). This finding implies that increase in age (old age) Total 240 100 of catfish farmers will increase the technical inefficiency of Mean Technical efficiency 53.49% catfish production system in the study area. This result col- Minimum Technical 46.01% laborates with the earlier report of Achoja et al. (2020) that efficiency Maximum Technical efficiency 71.21%

6 Aquat Res 4(1), 1-9 (2021) • https://doi.org/10.3153/AR21001 Research Article

The Technical Efficiency shows the ability of farmers to de- findings showed that profit efficiency ranged from 23 rive maximum output from the inputs used in catfish produc- percent to 99 percent with a mean efficiency of 84 percent. tion. Given the results of the Cobb-Douglas stochastic frontier model, the technical estimates are presented and dis- Production Constraints Faced by Catfish Farmers cussed in Table 3. The Technical efficiency of the sampled Some constraints were identified as hindrances to technical households is less than 1 indicating that all the households are efficiency of catfish production system in the study area. producing below the maximum efficiency frontier. A range These constraints include: lack of finance, acquisition of of technical efficiency is observed across the sampled house- Land, purchase of farming inputs, technical support holds where the spread is large. The best catfish household from government or local authorities, pollution and had a Technical Efficiency of 71.21%, while the worst house- environmen-tal/climate change. Among the various hold had a technical efficiency of 46.01%. The mean Tech- constraints that affect the level of productivity in the study nical efficiency was 53.49%. This implies that on the average, area, lack of finance was identified as the most serious the respondents were able to attain approximately 53.5% of challenge, followed by tech-nical support from optimal technical efficiency from a given set of inputs utili- government / local authorities. The result of this finding zation in catfish production system. This shows that catfish supports that of Tisdell (2003) who stated that the most farmers households Technical Efficiency can be improved by important factor inhibiting fish farmer’s productiv-ity in the 46.51% in order to raise the level of catfish technical effi- study area include lack of access to financial capital and high ciency in the study area. The finding tallies with the result cost of feed or other farm input. obtained by Tsue et al. (2012) in their study on profit efficiency among catfish farmers in Benue State, Nigeria. Their

Table 5. Production Constraints Faced by Catfish Producers Name Not a Minor Major Mean Remarks prob- problem Problem lem Lack of finance 7 26 47 2.50 Significant Acquiring land on which to farm 7 43 30 2.29 Significant Farming inputs(water, fingerlings, 5 59 16 2.14 Significant equipment and machinery) Technical support from government/lo- 44 31 2.33 significant cal authorities Pollution 37 19 1.94 Not significant Environmental/Climate Change 43 11 1.81 Not significant Cut off point=2.00 Mean>2.00=a problem, mean<2.00=not a problem

Aquat Res 4(1), 1-9 (2021) • https://doi.org/10.3153/AR21001 Research Article

Conclusion This study examines stochastic frontier of catfish aquaculture Compliance with Ethical Standard agribusiness for sustainable fisheries development in Nige- Conflict of interests: The authors declare that for this article they ria. It was found out that catfish farming in the study area is have no actual, potential or perceived conflict of interests. relatively young and there is hope for an increase in level of involvement among the people in the study area. The majority Ethics committee approval: The research was carried out with approval of the Ethical Committee of the Department of Agri- of those who were involved in catfish production were able cultural Economics and Extension, Delta state univer- bodied men in their active age bracket, hence the potential to sity, Asaba campus, Nigeria (06/07/2019). We (the au- sustain catfish farming for many more years. A positive net thors) hereby declare that this research does not include any ex- farm income with increased return per naira invested indi- periments with human or animal subjects cated that catfish farming in the study area was profitable. Funding disclosure: No funding was received from external bod- Quantity of fingerlings and fish feed negatively and posi- ies, institutions or agencies for the execution of this research. tively influencing the output of catfish respectively. The result shows that the modal class of the catfish farmers was Acknowledgments: We (the authors) hereby acknowledge all the within the productive age of 40-49 years. Catfish farmers had authors whose works were reviewed while conducting this study. obtained various levels of formal education. Finding shows We also appreciate our professional colleagues whose criticisms and contributions have added value to this article. that feeds cost was the highest variable cost. The result also revealed that the rate of return on investment was Disclosure: - 57.5%. The study revealed that for every $1.00 invested in catfish production, a net return of $0.57 is generated. Feed has a positive and significant relationship with catfish References output. Mean technical efficiency is 53.49%. The profit inef- Achoja, F.O., Gbigbi, T.M., Ikpoza, E.A., Denghan, J.E. ficiency is highly significant among catfish farmers. About (2020). The strategic participation of young people in 26% of the total variation in catfish profitability is due to shrimp farming value chain in Nigeria. Yüzüncü Yıl Üniver- technical inefficiency factors. The most significant efficiency sitesi Tarım Bilimleri Dergisi, 30(1), 197-203. factors are fish feed and pond size. Age of farmer, educational https://doi.org/10.29133/yyutbd.661848 attainment, lack of finance and technical support from government authorities are the most important inefficiency fac- Adewunmi A. A. and V.F. Olaleye (2011). Catfish culture tors that require urgent policy attention for sustainable catfish in Nigeria: Progress, prospects and problems”, African Jour- aquaculture development. nal of Agricultural Research, 6(6), 1281-1285.

Based on the findings of the study, the following recommen- Aigner D.J., C.A.K. Lovel and P. Schmidt, (1977). Formu- dations are hereby made to promote increased catfish produc- lation and estimation of stochastic frontier production function in the study area. tion models. Journal of Econometrics, 6(1), 21-37. Government should provide facilities such as incentives, sub- https://doi.org/10.1016/0304-4076(77)90052-5 sidies and facilitate access to credit by catfish farmers in the study area by the review of the stringent lending policies of Alawode O.O. and Jinad A.O. (2014). evaluation of tech- the formal lending institutions. Catfish farmers should come nical efficiency of catfish production in Oyo State: A case together to form co-operative unions to facilitate their access study of Ibadan Metropolis. Journal of Emerging Trends in to credit and other inputs. Adequate trainings and seminars Educational Research and Policy Studies, 5(2), 223-231. should be held at interval to update catfish farmers’ knowledge on the art of catfish farming so that they could Baruwa O.I, Omodara O.D (2019). Technical efficiency of have access to improved methods and technologies of catfish aquaculture system in Oyo State, Nigeria: Stochastic frontier production. Effort should be made to bring down the cost of approach. Journal of Aquatic Research & Marine Sciences, feeds by exploring alternative sources of feed for catfish 114-120. through well-funded research. https://doi.org/10.29199/ARMS.201026

FAO (2010). The State of World Fisheries and Aquaculture, Rome, pp.88, http://www.fao.org/3/a-i1820e.pdf, ISBN: 978- 92-5-106675-1

Aquat Res 4(1), 1-9 (2021) • https://doi.org/10.3153/AR21001 Research Article

FAO (2012). The State of World Fisheries and Aquaculture, Onoja A.O., Achike A.I. (2011). Resource productivity in Rome, pp. 209, http://www.fao.org/3/a-i2727e.pdf, ISBN: small-scale catfish (Claria gariepinus) farming in River state 978-92-5-107225-7. Nigeria: A translog model approach. Journal of Agricultural and Social Research, 11(2), 139 -146. Fourie, J.J. (2006). “A Practical Investigation into Catfish (Clarias gariepinus) Farming in the Vaalharts Irrigation Onu J.K., Amaze P.S., Okunmadewa F.Y., (2000). Deter- Scheme”, Department of zoology and Entomology, Univer- minants of cotton production and economic efficiency, Afri- sity of the Free State, Faculty of Natural and Agricultural Sci- can Journal of Business and Economic Resources, 1, 234- ences. 240.

Goksel A. (2008). Determining the factors affecting effi- Oyinbo O., Mohammed O.M., Falola A., Saleh M.K. ciency scores in agriculture. International Journal of Agricul- (2016). Technical efficiency of catfish farming in Alimosho tural Science, 3, 328-330. local government area of Lagos State, Nigeria: A gender per- https://doi.org/10.3923/ijar.2008.325.330 spective, Agricultura Tropica et Subtropica, 49, 45-49. https://doi.org/10.1515/ats-2016-0006 Kudi T.M., Baka F.P., Atala T.K. (2008). Economics of fish production in Kaduna State Nigeria. ARPN Journal of Revilla-Molina I.M., Bastiaans L., van Keulen H., Mew Agriculture and Biological Sciences, 5(5&6), 17-21. T.W., Zhu Y.Y. (2009). Improvement of technical efficiency in rice farming through interplanting: A stochastic frontier Obasi, P.C. (2000). The Determinants of Food Consumption analysis in Yunnan, China. DEGIT Conference Papers, DE- and Agricultural Productivity in Imo State Nigeria. Ph.D The- GIT, Dynamics, Economic Growth, and International Trade. sis, Federal University of Technology, Owerri, Nigeria. Sikiru B.O., Omobolanle N.M, Ayorinde B.J.O., Adegoke Okechi, J.K. (2004). Profitability Assessment A Case Study O.O. (2009). Improving clarias productivity. Journal of Bio- of Africa Catfish (Clarias gariepinus) Farming in the Lake logical Resources, 3(1-2), 24-28. Victoria Basin, Kenya United Nations University Fisheries Training Programme. Squires D., Grafton Q., Alam F., Omar H.I. (2003). Tech- nical efficiency in the Malaysian gillnet artisanal fisheries. Olasukanmi, J.B. (2012). Economic Analysis of Fish Farm- Environmental Development Economics, 8, 481-504. ing in Osun State, South Western Nigeria, Proceedings of the https://doi.org/10.1017/S1355770X0300263 International Institute of Fisheries Economics and Trade Tan- zania, pp. 1-10. Tisdell, C. (2003). Economics and marketing in aquaculture farming. Aquatic Animals and Plants. Blackwell Publishing Olujimi O.J. (2002). Economic Efficiency in the coastal Ltd, Oxford. ISBN 0-85238-22-7. Pp237-251 small scale fisheries in Lagos state, Nigeria, Federal College of Fisheries and Marine Technology, Victoria Island, pp. 1- Tsue, P.T., Lawal W.L., Ayuba, V.O. (2012). Profit Effi- 6. ciency among catfish farmers in Benue State, Nigeria. Afri- can Journal of Food, Agriculture, Nutrition and Develop- Ologbon A.C., Ambali I. (2012). Poultry enterprise combi- ment, 12(6), 6759-6775. nation among small-scale farmers in Ogun State, Nigeria: A technical efficiency approach. Journal of Agriculture and Williams S.B., Kareem R.O., Ojolowo O.A. (2012). Eco- Veterinary Sciences, 4(1), 7-15. nomic analysis of catfish production in Ile-Ife, Osun State, Nigeria. Journal of Human Ecology, 40(1), 1-7. https://doi.org/10.1080/09709274.2012.11906518

9 AQUATIC RESEARCH

E-ISSN 2618-6365

Aquat Res 4(1), 10-20 (2021) • https://doi.org/10.3153/AR21002 Research Article

İstanbul Boğazı’ndaki ticari gemi kazalarının karar ağacı yöntemiyle analizi

Erkan ÇAKIR , Bünyamin KAMAL

Cite this article as: Çakır, E., Kamal, B. (2021). İstanbul Boğazı’ndaki ticari gemi kazalarının karar ağacı yöntemiyle analizi. Aquatic Research, 4(1), 10-20. https://doi.org/10.3153/AR21002

Recep Tayip Erdoğan Üniversitesi, ÖZ Turgut Kıran Denizcilik Fakültesi, Rize, Türkiye Bu çalışmada İstanbul Boğaz bölgesi olarak İstanbul Gemi Trafik Hizmetlerinin kapsama alanına giren Tür- keli, Kandilli, Kadıköy ve Marmara sektörlerinde 2001-2016 yılları arasında meydana gelen ticari gemi ka- zaları incelemeye tabi tutulmuştur. Ulaştırma ve Altyapı Bakanlığı Ana Arama Kurtarma Koordinasyon Mer- kezi (AAKKM) veri tabanındaki kaza kayıtlarına uygulanan filtrelemeler sonucunda 500 groston üzeri ticari yük gemilerinin karıştığı 535 adet gemi kazası analiz edilmiştir. Belirtilen sektörlerde meydana gelen ticari ORCID IDs of the author(s): yük gemi kazaları Ki-kare Otomatik Etkileşim Dedektörü (CHAID) karar ağacı yöntemi ile incelenmiştir. E.Ç. 0000-0001-8486-3310 CHAID karar ağacı yöntemi sınıflandırma ve büyük veri kümelerinden anlamlı kurallar çıkarmada en yaygın B.K. 0000-0002-9885-114X kullanılan karar ağacı algoritmalarından biridir. CHAID karar ağacı yöntemi icra edilerek ticari yük gemilerinde meydana gelen kazaların tipi (çatışma/çatma, karaya oturma ve diğer) ile gemi faktörleri (gemi tipi, gemi boyu, gemi tonajı, gemi yaşı, gemi bayrağı, gemi yüklülük durumu), zaman faktörleri (kaza zamanı ve kaza mevsimi) ve diğer faktörler (kazanın meydana geldiği sektör, kaza nedeni ve gemiye pilot alınması durumu) arasındaki ilişki incelemeye alınmıştır. Kazanın meydana geldiği sektör, gemide pilot bulunması durumu, gemi tipi ve kaza zamanı kaza tipini etkileyen en önemli girdi değişkenleri olarak bulunmuştur. Veri setine uygulanan Karar Ağacı yöntemi sonucuna göre Kadıköy sektöründe meydana gelen kazaların % 86 Submitted: 01.06.2020 olasılıkla çatışma/çatma, Kandilli veyahut Marmara sektörlerinde meydana gelen kazaların % 48 olasılıkla Revision requested: 18.06.2020 çatışma/çatma ve Türkeli sektöründe ise kazaların % 36 olasılıkla çatışma/çatma ve diğer kaza tipleri ile Last revision received: 07.07.2020 sonuçlandığı görülmüştür. Accepted: 15.07.2020 Anahtar Kelimeler: İstanbul Boğazı, Gemi kazaları, Kaza analizi, Karar ağacı Published online: 21.10.2020 ABSTRACT

Analysis of merchant vessel accidents in Istanbul strait through decision tree method In this study merchant vessel accidents which occured between 2001 and 2016 in the sectors of Türkeli, Kandilli, Kadıköy, Marmara which constitutes Istanbul Strait region under Istanbul Vessel Traffic Services Correspondence: Bünyamin KAMAL scope have been examined. Data was obtained from database of Ministry of Transport and Infrastructure Main Search and Rescue Coordination Center, and after data cleansing process, 535 vessel accidents which E-mail: [email protected] involve merchant cargo vessels of above 500 grosston have been analyzed. Merchant cargo vessel accidents which were taken place in the specified sectors have been examined with CHAID (Chi-square Automatic Interaction Detector) Decision Tree method. CHAID Decision Tree method is one of the most common used decision tree algorithms in extracting meaningful rules from big datasets and for classification. Through conducting CHAID Decision Tree method for merchant vessel accidents relationship between accident type (collision/contact, grounding and other) and vessel factors (vessel type, Length overall (LOA), vessel gross ton- nage, vessel age, flag, loading condition), time factors (accident time, season of accident) and other factors (sector where accident occured, pilot on board or not) has been analyzed. Accident occuring sector, pilot on © 2021 The Author(s) board/not, vessel type and accident time have been found as the most important input variables. Based on the result of the Decision Tree method applied to the data set, it was observed that the accidents occurring in the Kadıköy sector were collision / contact with 86% probability, the accidents occurring in the Kandilli or Mar- mara sectors were collision / contact with 48% probability and in the Türkeli sector, both collision / contact Available online at and other accident types had 36% occurring probability. http://aquatres.scientificwebjournals.com Keywords: Istanbul Strait, Vessel accidents, Accident analysis, Decision tree

Aquat Res 4(1), 10-20 (2021) • https://doi.org/10.3153/AR21002 Research Article

Giriş Kuzeyde Anadolu Feneri ile Türkeli Feneri’nin birleştiği hat- miştir. Çalışmanın ikinci kısmında İstanbul Boğazında mey- tan başlayan ve güneyde ise Ahırkapı Feneri ile Kadıköy İn- dana gelen gemi kazaları ile ilgili yapılan literatür çalışmala- ceburun Feneri’nin birleştiği hatta son bulan İstanbul Boğazı rına yer verildikten sonra üçüncü kısımda çalışmada istihdam dünyanın en dar kanallarından birisidir ve yoğun bir deniz edilen veri setinin detayları verilmiştir. Akabinde ise verilerin trafiğine maruz kalmaktadır. Boğaz coğrafi yapısı ve oşinog- işlenmesinde kullanılan Ki-kare Otomatik Etkileşim Dedek- rafik özellikleri sebebiyle riskli bir suyoludur. Boğaz’ın orta- törü (CHAID) karar ağacı yöntemi açıklanmıştır. Bulgular lama genişliği 1500 metre iken en dar yeri 696 metredir ve en kısmında icra edilen yöntemin çıktıları verildikten sonra so- sığ yerde 19 metre derinliğe sahiptir (Özdemir, 2019). Kıv- nuç kısmında bazı öneriler yapılmıştır. rımsı yapısından dolayı Boğaz toplam sayıları 12’yi bulan İstanbul Boğazında meydana gelen kazalar bağlamında lite- keskin dönüşe sahiptir ve buna istinaden Kandilli’de 45°’lik, ratür incelendiğinde görülmektedir ki Sezgin F. ve Kadıoğlu Umur Bankı’nda 70°’lik ve Yeniköy’de ise 80°’lik büyük M. (2000) tarafından yapılan çalışma İstanbul Boğazı’nda açılı rota değişikliği yapılmaktadır (Akten, 2003; Ece, 2016). 1982 ile 1999 yılları arasında vuku bulan 218 kaza verisini Bu keskin dönüşlere ek olarak dipteki ve yüzeydeki ters akın- yıllara ve aylara ayırarak uygunluk analizi istatistiki yöntemi tılar seyir emniyetini ciddi bir şekilde etkilemekte ve zaman ile incelemiştir ve boğazda meydana gelen kazalar sebep, yer, zaman 6 ile 8 knota varan bir akıntı rejimi söz konusu olabil- meydana geldiği saat, kazaya müdahil olan geminin bayrağı, mektedir (Özdemir, 2019). tonajı ve türü gibi değişkenler bağlamında sınıflandırılmıştır. Karadeniz ülkelerinin ticaret hacimlerindeki ve filo hacimle- Akten (2003) çalışmasında 1953-2002 yılları arasında İstan- rinde artış, Tuna-Ren, Tuna-Main gibi iç suyollarının devreye bul Boğazı’nda meydana gelen 461 kazayı kaza türleri ve alınması ve son zamanlarda ölçek ekonomisinden istifade kaza zamanına (gece-gündüz) göre ayırmıştır. Otay N. E. ve amacına binaen gemi boyutlarında görülen artışlar Bo- Özkan Ş. (2005) çalışmalarında İstanbul Boğazında gemile- ğaz’dan taşınan yük miktarında artışa sebebiyet vermiştir rin çarpışma, sahile vurma ve karaya oturma olasılıklarını he- (Ece, 2011). Ulaştırma ve Altyapı Bakanlığı verilerine göre saplamıştır ve elde edilen sonuçlar ışığında İstanbul Bo- Boğaz’da taşınan tehlikeli yük miktarı yıldan yıla artış gös- ğazı’ndaki transit gemi trafiği için kaza olasılıklarının coğrafi termekte ve 2010 yılında taşınan tehlikeli yük miktarı yakla- olarak dağılımını gösteren risk haritalarını teşkil etmişlerdir. şık 359 milyon ton iken bu oran 2018 yılında yaklaşık 147 Bayar vd. (2008) İstanbul Boğazındaki kazaları Gemi Trafik milyon tonu tankerlerce taşınmak kaydıyla yaklaşık 439 mil- Sisteminin (VTS) etkisini görebilmek için VTS kurulumu ön- yon tona ulaşmıştır (Deniz Ticareti İstatistikleri, 2018). cesi ve sonrası dönemlerini baz alarak incelemiştir. VTS ön- Malaka Boğaz’ının ardından dünyanın en yoğun ve tehlikeli cesi periyodu 1985 ve 2003 yılları arası baz alınarak ve VTS trafiğine sahne olan İstanbul Boğazı Panama Kanalından sonrası periyodu 2004 ve 2008 yılları arası baz alınarak ince- yaklaşık 3 kat, Süveyş Kanalından 2 kat ve Kiel Kanalından lenmiştir. Çalışmada İstanbul Boğazında meydana gelen ka- 1.5 kat daha yoğun deniz trafiğine sahiptir (Kiel Canal, 2018; zalar gemi türlerine, bayrak ülkelerine ve kaza türlerine göre Panama Canal, 2019; Suez Canal, 2019). Ulaştırma ve frekans dağılımı ile sınıflandırılmıştır ve VTS’nin kazaları Altyapı Bakanlığı verilerine göre 8.957 adedi tanker olmak azaltmada etkili olup olmadığı değerlendirilmiştir. Ece üzere 2019 yılında 41.112 gemi geçişi gerçekleşmiştir (2011) ise İstanbul Boğazı’nda Sağ Seyir Düzeni’nin icra (Ulaştırma ve Altyapı Bakanlığı, 2019). edilmeye başlandığı 1982 yılından 2008 yılı sonuna kadar meydana gelen 341 kaza için kazaya karışan gemilerin adı, Emniyet kurallarındaki ve deniz taşımacılığındaki teknolojik tonajı, bayrağı, kaza saat, günü, ayı, yılı, kaza türü, kaza ne- gelişmelere rağmen kazalar vuku bulmaya devam etmekte, deni ve kazaya karışan geminin kılavuz kaptan istihdam edip önlenememekte ve ciddi bir sorun teşkil etmeye devam et- etmediği gibi bilgileri gibi değişkenleri ihtiva eden kaza veri mektedir (Erol ve Başar, 2015). Boğazın hem hidrolojik, je- tabanı teşkil edilmiştir. Bu değişkenlere ilişkin olarak frekans omorfolojik ve meteorolojik yapısı hem de yoğun deniz tra- dağılım tabloları teşkil edilmiş olup değişkenler arasındaki fiği ve beraberinde artan gemi tonajları ile taşınan tehlikeli ilişki için Ki-Kare İlişki Analizi gibi istatistiki analizler icra yükler deniz kazası riskini arttırmaktadır. Meydana gelen ka- edilmiştir. Ayrıca Boğazdaki gemi kazalarının önlenmesine zalar can/mal kaybına ve çevresel kirliliğe sebep olmaktadır. dair bazı önerilerde bulunulmuştur. Erol ve Başar (2015) ça- Boğaz’da meydana gelmekte olan deniz kazalarının önlen- lışmalarında Karadeniz, Marmara Denizi ile Akdeniz ve Ege mesi ve emniyetin tesisi için evvela bu kazaların farklı yön- Denizinin bir kısmından müteşekkil olan Türkiye Arama ve lerden analize tabi tutulması gerekmektedir. Bu amaç doğrul- Kurtarma sahasında 2001 ve 2009 yılları arasında vuku bulan tusunda ele alınan bu çalışma belirtilen sıra ile organize edil- 1247 deniz kazasını incelemiştir. Çalışmalarında Türkiye

Aquat Res 4(1), 10-20 (2021) • https://doi.org/10.3153/AR21002 Research Article

Arama Kurtarma sahası Trabzon, Samsun, İstanbul, Çanak- Sistemi istihdam edilmiştir. İstikbal (2020) Boğaz’da mey- kale, İzmir, Antalya ve Mersin olarak 7 bölgeye ayrılmıştır dana gelen 3 büyük gemi kazasını 1934-1982 yılları arasında ve elde edilen veriler frekans analizi ile sınıflandırılmış ve geçerli olan “Sol Seyir Düzeni” ile olan ilişkileri bağlamında karar ağacı yöntemi ile analiz edilmiştir. Ece (2016) frekans değerlendirmiştir. dağılımları, Ki-Kare İlişki Testi ve Cramer’s V Testi gibi istatistiksel analizleri yaparak İstanbul Boğaz’ında 1982 ile Materyal ve Metot 2014 yılları arasında meydana gelen kazalara karışan gemiler Veri Seti Detayları ile bunların kılavuz kaptan almaları arasındaki ilişkiyi incelemiştir. Erol vd. (2017) veri filtreleme işlemi sonucu Bo- Bu çalışmada, İstanbul Boğazı’nda 2001-2016 yılları ara- ğaz’da 2001-2015 yılları arasında meydana gelen 135 deniz sında meydana gelen deniz kazaları konu edilmiştir. Türkiye kazasını meteoroloji verilerini de hesaba katarak kaza şidde- Cumhuriyeti Ulaştırma ve Altyapı Bakanlığı Deniz ve İç Su- tine göre sınıflandırarak incelemiştir. Yılmaz ve İlhan (2018) lar Genel Müdürlüğü Ana Arama Kurtarma Koordinasyon çalışmalarında Ana Arama Kurtarma ve Koordinasyon Mer- Merkezi (AAKKM) sözü geçen yıllar arasında İstanbul Bo- kezinden elde edilen verilerle 2002 ile 2014 seneleri arasında ğazı’nda meydana gelen toplam 1091 deniz kazasını/olayını İstanbul Boğazı’nı da içerecek şekilde Türkiye arama-kur- kayıt altına almıştır. Bu 1091 deniz kazası/olayından 535 ta- tarma bölgesinde Türk bayraklı gemilerde veyahut Türk bay- nesi gerekli filtrelemelerden sonra çalışmaya dâhil edilmiştir. raklı gemilerin karıştığı ve ölüm, yaralanma veyahut kayıp ile 535 deniz kazası, 500 groston üstü ticari yük gemilerinin İs- sonuçlanan 182 adet deniz kazası/olayını istatistiki olarak tanbul Boğaz Bölgesi’ndeki Gemi Trafik Hizmetlerinin analiz etmişlerdir. Özdemir (2019) ise 2003 ile 2013 yılları (GTH) sürdürüldüğü ve aşağıdaki Şekil 1’de de görüldüğü arasında Türkiye Boğazlar Sistem’inde hasıl olan deniz üzere Kadıköy, Türkeli, Marmara ve Kandilli sektörlerinde kazalarını frekans ve mekansal analiz yöntemiyle genel meydana gelen kazaları kapsamaktadır. Balıkçı tekneleri, olarak ve boğazların sektörleri temelinde incelemiştir. Bu yolcu gemileri, gezinti tekneleri vb. kazaları çalışma kapsamı çalışmada kazalar İstanbul ve Çanakkale Gemi Trafik dışında tutulmuştur. Ayrıca çalışmada sadece gemi kazaları Hizmetleri bölgelerinde oluşan kazalar olarak iki bölümde ele alınıp gemilerde meydana gelen iş kazaları, sağlık sorun- değerlendirilmiştir ve mekansal analiz için Coğrafi Bilgi ları vb. deniz olayları incelenmemiştir.

Şekil 1. İstanbul GTH alanı ve sektörleri (KEGM, 2020) Figure 1. Istanbul VTS area and sectors (KEGM, 2020)

Aquat Res 4(1), 10-20 (2021) • https://doi.org/10.3153/AR21002 Research Article

Tablo 1’de çalışmada kullanılan değişkenler, değişkenlerin 2’de görüldüğü üzere çalışmada kullanılan 535 gemi kazası- değerleri (kategorileri) ve bunların kaza tipine göre dağılımı nın 385’inin çatışma/çatma, 83’ünün karaya oturma, 26’sının gösterilmiştir. Toplam 11 değişken AAKKM’nin kaza rapor- yangın/patlama, 21’inin alabora ve 20’sinin makine/ekipman ları incelenerek elde edilmiş olup bu çalışmada girdi (bağım- arızası olduğu görülmektedir. Kaza sayılarının yetersiz ol- sız) değişken olarak kullanılmıştır. Kaza tipi değişkeni ise ması nedeniyle yangın/patlama, makine/ekipman arızası ve çıktı diğer adıyla bağımlı değişken olarak ele alınmıştır. Şekil alabora tip gemi kazaları diğer kategorisi altında birleştirile- rek çalışmada kullanılmıştır. Tablo 1. Çalışmada kullanılan değişkenlerin kaza tipine göre dağılımı Table 1. Distribution of input variables according to accident type Toplam Kaza tipi Değişkenler Değerler Çatışma/ Karaya Diğer

Çatma oturma Gemi tipi Genel yük gemisi 359 (%67.1) 261 (%72.7) 54 (%15.0) 44 (%12.3) Dökme kuruyük gemisi 77 (%14.4) 59 (%76.6) 13 (%16.9) 5 (%6.5) Petrol tankeri 15 (%2.8) 6 (%40.0) 4 (%26.7) 5 (%33.3) Kimyasal tanker 25 (%4.7) 18 (%72.0) 3 (%12.0) 4 (%16.0) Konteyner 16 (%3.0) 10 (%62.5) 4 (%25.0) 2 (%12.5) Diğer 43 (%8.0) 31 (%72.1) 5 (%11.6) 7 (%16.3) Gemi yaşı [0-4] 32 (%6.0) 22(%68.6) 6 (%18.8) 4 (%12.5) [5-14] 46 (%8.6) 33 (%71.7) 8 (%17.4) 5 (10.9) [15-24] 94 (%17.6) 67 (%71.3) 15 (%16.0) 12 (%12.8) 25+ 363 (%67.9) 263 (%72.4) 54 (%14.9) 46 (%12.7) Gemi grosston [500-10.000] 431 (%80.6) 312 (%72.4) 62 (%14.4) 57 (%13.2) 10.000+ 104 (%19.4) 73 (%70.2) 21 (%20.2) 10 (%9.6) Gemi tam boyu (m) [0-100] 216 (%40.4) 143 (%66.2) 45 (%20.8) 28 (%13.0) 100+ 319 (%59.6) 242 (%75.9) 38 (%11.9) 39 (%12.2) Gemi yüklülük durumu Dolu 175 (%32.7) 124 (%70.9) 27 (%15.4) 24 (%13.7) Boş 360 (%62.3) 261 (%72.5) 56 (%15.6) 43 (%11.9) Gemi bayrağı T.C. 133 (%24.9) 94 (%70.7) 22 (%16.5) 17 (%12.8) Kolay bayrak (FOC) 330 (%61.7) 241 (%73.0) 49 (%14.8) 40 (%12.1) Diğer 72 (%13.5) 50 (%69.4) 12 (%14.5) 10 (%13.9) Gemide pilot durumu Var 213 (%39.8) 122 (%57.3) 48 (%22.5) 43 (%20.2) Yok 322 (%60.2) 263 (%81.7) 35 (%10.9) 24 (%7.5) Kaza zamanı Gündüz 216 (%40.4) 147 (%68.1) 30 (%13.9) 39 (%18.1) Gece 319 (%59.6) 238 (%74.6) 53 (%16.6) 28 (%8.8) Kaza mevsimi İlkbahar 105 (%19.6) 72 (%68.6) 19 (%18.1) 14 (%13.3) Yaz 86 (%16.1) 58 (%67.4) 16 (%18.6) 12 (%14.0) Sonbahar 142 (%26.5) 98 (%69.0) 26 (%18.3) 18 (%12.7) Kış 202 (%37.8) 157 (%77.7) 22 (%10.9) 23 (%11.4) Kaza sektörü Kadıköy 357 (%66.7) 307 (%86.0) 29 (%8.1) 21 (%5.9) Kandilli 61 (%11.4) 29 (%47.5) 20 (%32.8) 12 (%19.7) Marmara 31 (%5.8) 16 (%51.6) 9 (%29.0) 6 (%19.4) Türkeli 86 (%16.1) 33 (%38.4) 25 (%29.1) 28 (%32.6) Kaza nedeni İnsan hatası 147 (%27.5) 118 (%80.3) 17 (%11.6) 12 (%8.2) Makine/ekipman arızası 52 (%9.7) 20 (%38.5) 18 (%34.6) 14 (%26.9) Çevresel faktörler 136 (%25.4) 100 (%73.5) 23 (%16.9) 13 (%9.6) Bilinmiyor 200 (%37.4) 147 (%73.5) 25 (%12.5) 28 (%14.0)

Aquat Res 4(1), 10-20 (2021) • https://doi.org/10.3153/AR21002 Research Article

Yangın/patlama 26

Ekipman/makine arızası 20

Alabora 21 Kaza tipi Kaza Karaya oturma 83

Çatışma/çatma 385

0 50 100 150 200 250 300 350 400 450 Kaza sayısı

Şekil 2. İstanbul Boğazı’nda Meydana Gelen Kazaların Kaza Tipine Göre Dağılımı Figure 2. Distribution of vessel accidents occurred in Istanbul Strait according to accident type

Karar Ağaçları ve Ki-kare Otomatik Etkileşim Dedektörü nün) bir sınıf etiketi içerdiği akış şeması benzeri bir ağaç ya- (CHAID) Algoritması pısıdır. Bir ağaçtaki en üstteki düğüm kök düğümdür (Han ve Pei, 2012). Karar ağaçları finans, pazarlama, mühendislik ve Bu çalışmada, 2001-2016 yılları arasında İstanbul Boğazı tıp gibi uygulamalı alanlarda sıklıkla kullanılmaktadır (Ro- Bölgesi’nde meydana gelen ticari yük gemisi kazaları Ki- kach ve Maimon, 2008). Sınıflandırma ve büyük veri küme- kare Otomatik Etkileşim Dedektörü (CHAID) karar ağacı lerinden anlamlı kurallar çıkarmak amacıyla kullanılan C5.0, yöntemi ile IBM SPSS Modeler 18.0 kullanılarak analiz edil- CART, CHAID, QUEST vb. birçok karar ağacı algoritması miştir. Veri seti % 65’i eğitim ve % 35’i test amacıyla kulla- mevcuttur. CHAID bu algoritmalar içinde en yaygın kullanı- nılmak üzere ikiye bölünmüştür. Eğitim veri seti, model pa- lanlardan biridir (Lin ve Fan, 2019). rametrelerini tahmin etmek ve modeli oluşturmak için kulla- nılırken, test veri seti modeli bağımsız verilere uygulanabilir- Kass (1980) tarafından ortaya çıkarılan CHAID, karar ağa- liğini ve modelin genelleme yeteneğini test etmek için kulla- cında ikiden çok bölünmeler oluşturulmasını sağlayan bir tür nılmaktadır. CHAID karar ağacı yöntemi kullanılarak ticari makine öğrenme algoritmasıdır. CHAID, bir veri kümesini yük gemilerinde meydana gelen kazaların tipi (ça- girdi değişkenleri (bağımsız değişken) ile çıktı değişkenleri tışma/çatma, karaya oturma ve diğer) ile gemi faktörleri (bağımlı değişken) arasındaki ilişkiler temelinde alt gruplara (gemi tipi, gemi boyu, gemi büyüklüğü, gemi yaşı, gemi bay- ayırır (Prati ve diğerleri, 2017). Algoritma temel olarak diğer rağı, gemi yüklülük durumu), zaman faktörleri (kaza zamanı Karar Ağaçları algoritmaları ile benzer özelliklere sahiptir, ve kaza mevsimi) ve diğer faktörler (kazanın meydana geldiği ancak ki-kare bağımsızlık testi kullanılarak ağacı bölmelere sektör, kaza nedeni ve gemide pilot durumu) arasındaki ilişki ayırır (Mistikoglu ve diğerleri, 2015; Han ve Pei, 2012). Girdi incelenmiştir. değişkenlerinin her biri ile çıktı değişkeni arasındaki çapraz tablolar, ki-kare testi kullanılarak incelenir ve CHAID en Karar ağacı, hem sınıflandırıcıları hem de regresyon model- önemli girdi değişkenini seçer. Bir girdi değişkeninin ikiden lerini göstermek amacıyla kullanılabilen bir tahminleme yön- fazla kategorisi varsa, CHAID karşılaştırma kategorileri kar- temidir (Rokach ve Maimon, 2008). Bu yöntemin temel şılaştırır ve sonuçta hiçbir farkı olmayanlar bir araya getirilir amacı; büyük bir veri kümesinden anlamlı ve kullanılabilir (Prati ve diğerleri, 2017). Nihai CHAID karar ağacı, girdi de- bilgiler çıkarabilmektir (De Oña ve diğerleri, 2013). Karar ğişkenleri ile çıktı değişkenleri arasında anlamlı bir ilişki kal- ağacı, her iç düğümün (yapraksız düğüm) bir öznitelik üze- mayınca sonlandırılır. rinde bir testi temsil ettiği, her dalın testin bir sonucunu temsil ettiği ve her bir yaprak düğümünün (veya terminal düğümü- CHAID, her bir düğümde ikiden fazla dalı olan ağaçları inşa edebilmesi açısından diğer sınıflandırma yöntemlerine göre

Aquat Res 4(1), 10-20 (2021) • https://doi.org/10.3153/AR21002 Research Article

çeşitli avantajlar sağlar (Luna veMéndez, 2006; SPSS, 1998). rak bu bölünme işlemi karar ağacında başka bir anlamlı bö- Diğer karar ağacı algoritmalarının aksine, bölünme sonucu lünme ortaya çıkmayacak duruma gelene kadar devam eder. ortaya çıkan dal sayısının ikiden fazla olması, ağaç yapısının Bu sayede CHAID, bir dizi eğer-ise -değilse kuralını (if – daha kolay anlaşılır ve yorumlanabilir olmasına olanak verir then – else rules) kullanarak ticari yük gemi kazalarının ça- (Virens, 2001). Bununla birlikte hem kategorik hem de sü- tışma/çatma, karaya oturma ve diğer olarak sonuçlanma du- rekli değişkenlerle çalışabilmesi CHAID algoritmasına kulla- rumu hakkında oluşturduğu karar ağacı yapısı ile detaylı bil- nımı açısından esneklik sağlamaktadır (Althuwaynee ve di- giler sağlar. ğerleri, 2016). Ayrıca, girdi ve çıktı değişkenleri arasındaki Şekil 3’de girdi değişkenlerinin modeldeki göreceli önem de- ilişkiyi incelemek için parametrik teste ihtiyaç duyulmaması recesi diğer adıyla öngörü değeri normalize edilmiş haliyle ve verinin normal dağılımı şartının aranmaması CHAID al- verilmiştir. Her bir girdi değişkeninin önem derecesi, sonuç goritmasının diğer önemli avantajlarıdır (Díaz-Pérez ve Bet- (bağımlı) değişkeninin varyansındaki azalmanın duyarlılık hencourt-Cejas, 2016; Althuwaynee ve diğerleri, 2016). analizi yoluyla hesaplanması sonucu elde edilir. Kazanın Bulgular ve Tartışma meydana geldiği sektör (100), gemide pilot bulunma durumu (23), gemi tipi (16) ve kaza zamanı (12), kaza tipinin belir- Daha önce belirtildiği gibi, CHAID algoritması, karar ağacı lenmesinde en önemli girdi değişkenleri olarak bulunmuştur. oluşturmak için kullanılan bir sınıflandırma yöntemidir. Bir Bununla birlikte, girdi değişkenlerinin önem değeri, tek ba- karar ağacı, girdi değişkenleri (gemi tipi, kaza zamanı, kaza şına yordama güçlerinin altındaki mantığı anlamak için ye- sektörü, vb.) ve çıktı değişkeni (kaza tipi) arasındaki ilişkiler terli değildir. Bu yüzden, CHAID'in tahminleri hakkında temelinde bir veri kümesini alt gruplara ayırır. Her ağaç dü- daha derin bir fikir edinmek için karar ağacı yapısının ve or- ğümünde veriler, bir girdi değişkeninin değerleri ile iki veya taya çıkarılan kuralların incelenmesi gerekir. daha fazla farklı gruba özyineli olarak bölünür ve sonuç ola-

120 100

100

40 23

Normalize edilmiş önem yüzdesi önem edilmiş Normalize 16 20 12 7 5

0 Gemi grosstonu Gemi yüklülük Kaza zamanı Gemi tipi Pilot durumu Kaza sektörü durumu Değişkenler

Şekil 3. Değişkenlerin Normalize Edilmiş Önem Yüzdesi Figure 3. Normalized importance of input variables

Aquat Res 4(1), 10-20 (2021) • https://doi.org/10.3153/AR21002 Research Article

Şekil 4’de ticari yük gemi kazalarının hangi tür kaza tipi ile (geminin su üzerinde kalan kısmı) çok olması, dümen dinle- sonuçlandığını belirten son ağaç yapısı görülmektedir. Karar mesinin iyi olmaması, boğazdaki akıntıdan daha fazla etki- ağacı yapısı kaza sektörü, pilot durumu, kaza zamanı, gemi lenme ve geminin yapısal durumlarının (makine, boy, dizayn, tipi, gemi doluluk durumu ve gemi grostonu olmak üzere top- tip vs.) balastlı gemide aleyhe işlemesi gibi unsurlarla izah lam altı bölünmeye neden olan değişken içermektedir. 0 dü- edilebilir. Ayrıca dolu gemilerin yapmış olduğu 62 kazadan ğümündeki ilk bölünme, ticari yük gemisi kazalarını üç gruba 6’sı karaya oturma iken, boş gemiler için 89 kazadan sadece ayıran kaza sektörü ile meydana gelmiştir. Bu bölünmeye 2’sinin karaya oturma olduğu tespit edilmiştir. Son olarak göre, kazanın meydana geldiği yer Kadıköy sektörü oldu- ağacın beşinci seviyesinde, yüklü gemilerin yapmış olduğu ğunda kazalar %86 olasılıkla çatışma/çatma ile kazanın mey- kazalar, gemi grostonuna göre 10.000 groston üstü gemiler dana geldiği yer Kandilli veya Marmara sektörleri olduğunda ve [500-10.000] groston arasındaki gemiler olmak üzere iki kazalar %48 olasılıkla çatışma/çatma ile ve kazanın meydana terminal düğüme ayrılmıştır. 10.000 groston üstü gemilerin geldiği yer Türkeli sektörü olduğunda ise kazalar %36 olası- geçirmiş olduğu 13 kazanın 9’u çatışma/çatma, 4’ü ise karaya lıkla çatışma/çatma ya da diğer kaza tipleri ile sonuçlanmıştır. oturma kazası olarak bulunmuştur. Yüksek kapasiteli gemi- Burada çatışma/çatma olasılığının Kadıköy sektöründe yük- lerde çatışma/çatma oranının yüksek olması bu gemilerin dö- sek olması bir nebze buranın Boğaz bölgesindeki en yoğun nüş çapının artması ile ilintilendirilebilir. Diğer tarafta ise deniz trafiğine sahip bölge olması ile izah edilebilir. Zira Ka- [500-10.000] groston arasındaki gemilerin yapmış olduğu ka- dıköy sektörü Boğaz’ın güney girişini temsil etmektedir ve zaların yaklaşık %92’sinin çatışma/çatma ile sonuçlandığı bölgede yer alan Kartal ve Ahırkapı demir sahalarında demir- görülmüştür. Bu bağlamda belirtilebilecek önemli bir husus leme yapan çok sayıda gemi bulunmaktadır (Özdemir, 2019). şudur ki düşük tonajlı gemi zabitlerinin ehliyetinin yakın yol ehliyeti olma oranı yüksektir ve burada personel kalifikasyo- Karar ağacının ikinci seviyesinde, Kadıköy sektöründe mey- nunun yetersiz olmasının negatif bir rol oynadığı düşünül- dana gelen ticari gemi kazaları, gemide pilot olma durumuna mektedir. göre ikiye bölünmüştür. Eğer Kadıköy sektöründe kaza yapan gemilerde pilot mevcut ise çatışma/çatma kazası meydana CHAID Karar Ağacı yapısının ikinci seviyesinde Türkeli gelme olasılığı %73 iken, gemide pilot olmaması durumunda sektöründe meydana gelen kazalar, kaza zamanı değişkenine ise çatışma/çatışma kazası olasılığı %92’ye yükselmiştir. Bo- göre gece ve gündüz olmak üzere iki alt gruba ayrılmıştır. Bu ğaz geçişlerinde kılavuz kaptan istihdam etmeyen gemilerin bölünmeye göre, Türkeli sektöründe gece meydana gelen ka- kazalara karışma oranının artması Ece (2016) çalışmasında zalar %47 olasılıkla çatışma/çatma, %29 olasılıkla karaya da teyit edilmiştir. Zira gemi kazaları çok yüksek bir oranda oturma ve %23 olasılıkla diğer kaza tipi olduğu görülmüştür. insan hatasından kaynaklanmaktadır ve Boğaz’ı iyi bilen, Aynı sektörde gündüz meydana gelen kazaların %59’u diğer, yüksek tecrübe, eğitim seviyesi ve uzmanlığa sahip kılavuz %22’si karaya oturma ve %18’inin çatışma/çatma olduğu tes- kaptanların alınması personel hatalarından kaynaklanan ka- pit edilmiştir. Türkeli sektöründe çatışma/çatma tipi ticari zaları minimize etmektedir. Ağacın üçüncü seviyesinde, Ka- gemi kazalarının geceleri meydana gelme olasılığının gündüz dıköy sektöründe gemiye pilot almadan seyir yapan ticari ge- vakitlerine kıyasla daha yüksek olduğu görülmektedir. Bu du- milerin yapmış olduğu kazalar gemi tipine göre diğer gemiler rum vardiya tutan personelde durumsal farkındalık eksikliği ve genel yük; dökme kuru yük; kimyasal tanker; petrol tan- yani algıların azalması ile izah edilebilir. Zira personelin yor- keri; Ro-Ro; konteyner gemileri olmak üzere iki alt gruba ay- gunluğu ile beraber Boğaz manzarası ve insan popülasyonu rılmıştır. Diğer gemilerin yaptığı altı kazadan dördü ça- bu bağlamda vardiya zabitinin dikkatini dağıtıcı bir unsur ola- tışma/çatma diğer ikisi ise diğer kaza tipleri ile sonuçlanmış- rak negatif katkıda bulunduğu düşünülmektedir. Buna ek ola- tır. Dökme kuru yük; kimyasal tanker; petrol tankeri; Ro-Ro rak köprü üstünde görevli olmayan gemi personelinin fotoğ- veya konteyner gemilerinin yaptığı kazaların ise %93 olası- raf veya telefon görüşmeleri yapmak için köprü üstü civa- lıkla çatışma/çatma olduğu tahmin edilmiştir. Ağacın dör- rında bulunarak dikkat dağıtıcı hareketlerde bulunmaları da düncü seviyesinde, diğer gemi tipleri sınıfı haricindeki gemi- bu minvalde belirtilebilir. Ayrıca Boğaz trafiğine dâhil olan lerin yapmış olduğu kazalar geminin doluluk/yüklülük duru- balıkçı gemisi, yat veya tur motoru kaptanlarının ticari gemi- muna göre boş gemi ve dolu gemi olmak üzere iki alt gruba lerin geçiş üstünlüğüne engel olacak şekilde manevra yapma- ayrılmıştır. Dolu gemiler için %87 olan çatışma/çatma kazası ları veya çatışmayı önleme kurallarına aykırı manevraları ile olasılığının, boş gemiler için %97’ye çıktığı görülmüştür. beraber eksik iletişim de bu durumu bir nebze izah etmekte- Kargo taşımayan gemilerin yüklü gemilere kıyasen daha dir. Bu bağlamda son husus olarak gece özellikle Boğaz kıyı- fazla çatışma/çatmaya müdahil olması rüzgar etkisine daha sındaki sahil ışıklarının vardiya zabiti/kaptanın görüşünü açık olması, pervanesinin daha az batık olması, fribordunun olumsuz etkilediği belirtilebilir.

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Bu çalışmada dikkate alınan değişkenler yukarıda belirtilen- sonuç düğümündeki frekans sayısının asgari 5 olarak belirler ile sınırlıdır. Öte yandan belirtilmelidir ki karar ağacında lenmesi Kandilli/Marmara ve Türkeli sektöründe daha fazla değişkene ait yeterli bölünme sağlanabilmesi için her bir de- dal oluşmasına engel teşkil etmiştir. Buna istinaden, çalış- ğişkene ait olan değer sayısının yeterli frekansa sahip olması mada daha ziyade Kadıköy sektörü üzerine yoğunlaşılmıştır. gerekmektedir. Bu çalışmada, Kadıköy sektöründe meydana Bir sonraki çalışmada Uluslararası Denizcilik Örgütü’nün de- gelen kaza sayısı 357 iken, Kandilli/Marmara sektöründe top- niz kazalarının şiddeti-seviyesi hususunda yaptığı çok ciddi lam kaza sayısı 92 ve Türkeli sektöründeki mevcut kaza sa- deniz kazası, ciddi deniz kazası ve deniz olayı gibi bir sınıf- yısının 86 olması ağaç yapısının bu şekilde oluşmasına neden landırmayı temel alarak ve kazaya sebebiyet veren unsurların olmuştur. Ayrıca karar ağacında meydana gelen bölünmeler da AAKKM’den kaza bazlı derlenip hesaba katılması ile bu sonucu elde edilen kurallardaki vaka sayısının az olması, bu çalışmanın daha bütüncül bir analiz yapmaya daha elverişli kuralın genel kabul edilebilirliğini olumsuz etkilemektedir. hale geleceği düşünülmektedir. Bu yüzden, CHAID karar ağacı uygulaması öncesinde her bir

Şekil 4. CHAID Karar Ağacı Yapısı Figure 4. CHAID decision tree structure

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Sonuç nıflandırmasına dayalı verilerin de çalışmada dikkate alın- ması daha bütüncül bir değerlendirme yapmak için önem arz İstanbul Boğaz’ı uluslararası taşımacılık bağlamında stratejik etmektedir. öneme sahip alternatifsiz bir suyoludur. Özellikle Karadeniz bölge ülkelerinin denizyolu çıkış kapısıdır ve bu boğazda meydana gelebilecek kazalar Boğaz gemi trafiğini ciddi ma- Etik Standart ile Uyumluluk nada sekteye uğratabilir. Bu nihayetinde bölge ülkelerinin Çıkar çatışması: Yazarlar herhangi bir çıkar çatışmasının olmadı- ekonomilerine ciddi bir zarar verebilme potansiyeli ihtiva et- ğını beyan eder. mekle beraber can kayıplarına ve çevre felaketlerine de yol açabilir. Bu bağlamda, kazaların önlenmesi hususunda poli- Etik kurul izni: Bu çalışma için etik kurul iznine gerek yoktur. tika yapıcıların alacağı önlemlerin daha efektif olabilmesi Finansal destek: - için kazaların etkili ve kapsamlı bir şekilde analiz edilmesi ve Teşekkür: - değerlendirilmesi gerekmektedir. Bu kapsamda icra edilen çalışmada AAKKM’den elde edilen verilerle dört sektörden Açıklama: - teşekkül olan İstanbul Boğaz Bölgesi’nde 2001-2016 yılları arasında 500 groston üzeri ticari yük gemilerinin karıştığı 535 adet gemi kazası (CHAID) karar ağacı yöntemi ile incelen- Kaynaklar miştir. CHAID Karar Ağacı vesilesi ile ticari yük gemileri Akten, N. (2003). The Strait of Istanbul (Bosphorus): The için çıktı değişkeni olan kaza tipi ile gemi tipi, kaza zamanı, seaway separating the continents with its dense shipping traf- kaza sektörü vs. gibi girdi değişkenleri arasındaki ilişkiler in- fic. Turkish J. Marine Sciences, 9(3), 241-265. celenmiştir ve en önemli girdi değişkenleri olarak kazanın ol- duğu sektör, gemiye pilot alınması durumu, gemi tipi ve kaza Althuwaynee, O. F., Pradhan, B., Lee, S. (2016). A novel zamanı tespit edilmiştir. Bunu takiben görülmektedir ki en integrated model for assessing landslide susceptibility map- yüksek çatışma/çatma olasılığı Kadıköy sektöründe iken bu ping using CHAID and AHP pair-wise comparison. Interna- olasılık Kandilli/Marmara sektörlerinde düşüş göstermekte tional Journal of Remote Sensing, 37(5), 1190-1209. ve Türkeli sektöründe en düşük orana sahip olmaktadır. Ka- https://doi.org/10.1080/01431161.2016.1148282 dıköy sektöründe pilot istihdam etmeden ve yüklü olarak seyir yapan ticari gemilerden genel yük, dökme kuru yük, kim- Bayar, N., Özüm, S., Yılmaz, H. (2008). Analysis of Acci- yasal tanker, petrol tankeri, Ro-Ro ve konteyner gemilerinde dents in Istanbul Strait. http://web.deu.edu.tr/mari- çatışma/çatma kazası olasılığı %87 iken bu oran boş gemiler time/imla2008/Papers/43.pdf için % 97’ye çıkmaktadır. Ayrıca, Türkeli sektöründe gece Erişim Tarihi: 15.04.2020 oluşan kazalarda çatışma/çatma olasılığı gündüz meydana gelen kazalara kıyasen daha yüksek olduğu görülmekte iken De Oña, J., López, G., Abellán, J. (2013). Extracting deci- karaya oturma olasılığı çok düşük bir oranla gece daha yük- sion rules from police accident reports through decision sek çıkmaktadır. Diğer taraftan gemiye pilot almadan Boğaz trees. Accident Analysis & Prevention, 50, 1151-1160. geçişi yapan ticari yük gemilerinin pilot alarak seyir yapan https://doi.org/10.1016/j.aap.2012.09.006 gemilere kıyasla yaklaşık iki kat daha fazla kazaya karışmış olduğu görülmüştür. Bu bağlamda, Boğaz’daki seyir emniye- Deniz Ticareti İstatistikleri (2018) Filo, Denizyolu Taşıma, tinin iyileştirilmesi ve kaza riskinin azaltılması amacına bi- Teşvik, Gemi Sanayi, Gemi Denetim, Türk Boğazları Geçiş naen İdare’nin gemilerin pilot almasını teşvik edici bir rol oy- İstatistikleri. https://denizcilik.uab.gov.tr/uploads/pages/ya- naması gerekmektedir. Bu çalışmada ulaşılan sonuçların bo- yinlar/deniz-ticaret-2018-istatistikleri.pdf ğaz geçişini sık kullanan armatörlerin yanında tekne & ma- Erişim Tarihi: 15.03.2020 kine ve emtea sigortacıları ile donatanın üçüncü partilere karşı mesuliyetini teminat altına alan Koruma ve Tazminat Díaz-Pérez, F.M., Bethencourt-Cejas, M. (2016). CHAID (P&I Club) Kulüplerinin risk değerlendirmesinde ve adil bir algorithm as an appropriate analytical method for tourism prim seviyesinin tespitinde dikkate alması öngörülmektedir. market segmentation. Journal of Destination Marketing & Bir sonraki çalışmada kazaya sebebiyet veren unsurlar olarak Management, 5(3), 275-282. insan hatası, arızalar ve kazanın meydana geldiği andaki hava https://doi.org/10.1016/j.jdmm.2016.01.006 durumu gibi verilerin ve kazanın şiddeti bağlamında IMO sı-

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Ece, N.J. (2011). İstanbul Boğazı’nda meydana gelen deniz https://www.gdws.wsv.bund.de/SharedDocs/Down- kazalarının incelenmesi ve analizi. Dokuz Eylül Üniversitesi loads/DE/Publikationen/NOK_englisch.pdf?__blob=publi- Denizcilik Fakültesi Dergisi, 3(2), 37-59. cationFile&v=4 Erişim Tarihi: 22.06.2020

Ece, N.J. (2016). Kılavuzluk hizmetlerinin deniz emniyetine Lin, C.L., Fan, C.L. (2019). Evaluation of CART, CHAID, katkısı: İstanbul Boğazı’nda kazaya karışan gemiler ile and QUEST algorithms: a case study of construction defects kılavuz kaptan almaları arasındaki ilişkinin analizi. Journal in Taiwan. Journal of Asian Architecture and Building Engi- of ETA Maritime Science, 4(1), 3-21. neering, 18(6), 539-553. https://doi.org/10.1080/13467581.2019.1696203 Erol, S., Başar, E. (2015). The analysis of ship accident occurred in Turkish search and rescue area by using decision Mistikoglu, G., Gerek, I.H., Erdis, E., Usmen, P.M., tree. Maritime Policy & Management, 42(4), 377-388. Cakan, H., Kazan, E.E. (2015). Decision tree analysis of https://doi.org/10.1080/03088839.2013.870357 construction fall accidents involving roofers. Expert Systems with Applications, 42(4), 2256-2263. Erol, S., Demir, M., Çetişli, B., Eyüboğlu, E. (2018). Anal- https://doi.org/10.1016/j.eswa.2014.10.009 ysis of ship accidents in the Istanbul Strait using neuro-fuzzy and genetically optimised fuzzy classifiers. The Journal of Otay, N.E., Özkan, Ş. (2005). “Risk Map for the Strait of Navigation, 71(2), 419-436. Istanbul,” Proc. of the 5th Natl Conf on Coastal Engineering, https://doi.org/10.1017/S0373463317000601 May 2005, p19-32.

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20 AQUATIC RESEARCH

E-ISSN 2618-6365

Aquat Res 4(1), 21-37 (2021) • https://doi.org/10.3153/AR21003 Research Article

Community structure of mayflies (Insecta: Ephemeroptera) in tropical streams of Western Ghats of Southern India

Sivaruban BARATHY1 , Thambiratnam SIVARUBAN2 , Muthukumarasamy ARUNACHALAM3 , Pandiarajan SRINIVASAN2

Cite this article as: Barathy, S., Sivaruban, T., Arunachalam, M., Srinivasan, P. (2021). Community structure of mayflies (Insecta: Ephemeroptera) in tropical streams of Western Ghats of Southern India. Aquatic Research, 4(1), 21-37. https://doi.org/10.3153/AR21003

1 Fatima College, Department of Zoology, ABSTRACT Madurai, 625018, India. The main objective of this study was to evaluate the community structure of the order Ephem- 2 The American College, PG& Research department of Zoology, Madurai, eroptera in the Southern Western Ghats ecoregion along with Principal Component Analysis 625002, India (PCA) and Canonical Correspondence Analysis (CCA) from 2017 to 2018. Ecological param- 3 Central University of Kerala, School of eters estimated at each collecting site were pH, dissolved oxygen, biological oxygen demand, Biological Sciences, Department of hardness and alkalinity. This research investigation was carried out in 30 streams of Palni and Animal Science/Zoology Periyae-671 Cardamom hills in Western Ghats of Southern India. With PCA examination, the sites like 236, Kasargod, Kerala India Dhobikana, Fern hill and Poomparai of Palni hills are plotted far apart and are not supported by the ecological parameters like in the other sites. Dhobikana of Palni hills is exceptionally ORCID IDs of the author(s): contaminated in light of the fact that dhobis are associated with washing garments so cleanser S.B. 0000-0002-9464-6464 contamination is prevalent around there. In cardamom hills, Santhamparai near bridge and T.S. 0000-0001-8997-9355 Nayamakkadu are left far apart indicating they are not supported by physico-chemical param- M.A. 0000-0003-3979-2829 eters, mainly due to pollution. From to the CCA results, it is discovered that Baetis species P.S. 0000-0001-8118-3256 favor β-mesosaprobic habitat and Indialis badia inclines toward high altitudinal region. From the outcomes, it is presumed that pH, dissolved oxygen, biological oxygen demand, hardness and alkalinity were the essential components administering the mayfly community and struc- Submitted: 05.06.2020 ture. Revision requested: 16.07.2020 Keywords: PCA, Dhobikana, Dissolved oxygen, pH, Baetis, Ephemera nadinae Last revision received: 27.07.2020 Accepted: 30.07.2020 Published online: 12.11.2020

Correspondence: Sivaruban BARATHY E-mail: [email protected]

Available online at http://aquatres.scientificwebjournals.com

Aquat Res 4(1), 21-37 (2021) • https://doi.org/10.3153/AR21003 Research Article

Introduction Ephemeroptera also called as mayflies and they are cosmo- Analysis (CCA) to establish the community structure of may- politan in distribution (Barber-James et al., 2008). They do flies and Principal Component Analysis (PCA) to find the re- secondary production activity in freshwater habitat. Most lationship between stations and environmental parameters. families of mayflies are sensitive to pollution and they inhabit Multivariate investigation strategies have just been utilized to only in freshwater environment, so they serve as bio indica- consider the connection between benthic macroinvertebrate tors of water quality. community and ecological factors in all around the globe from the previous studies (Kazanci et al., 2017; Duran and Streams and rivers are an example of an important habitat and Akyildiz, 2011). As Palni and Cardamom hills belongs to the source of water for all living organism and human being. Pol- southern part of the Western Ghats, which is one of the eight lution either by anthropogenic activity or by nature can unfa- hottest hotspots in the globe (Myers et al., 2000) and no work vorably influence any biological ecosystem. The pollution in had to be done in the population dynamics and community the freshwater ecosystem affects the mayfly’s richness and structure of mayflies in this part of Western Ghats, so this diversity. Streams become contaminated by water entering work aims to assess the relationship between mayfly commu- from the farming area or modern destinations, and the nature nity and environmental factors in Palni and Cardamom hills of the water will be reflected by the kinds of the animals that of Western Ghats. can endure such as mayflies. Material and Methods The ecological attributes like pH, turbidity, dissolved oxygen, air temperature, water temperature, alkalinity, total dissolved Study Area solids and various pollutants legitimately and by implication Mayfly nymphs were collected from 2017- 2018 in thirty influence the mayfly populations. Deforestation is one of the sites (16 from Palni hills and 14 from Cardamom hills) using primary threats to mayfly biodiversity and conservation in the 1m wide Kick-net (Burton and Sivaramakrishnan, 1993) with tropics (Benstead and Pringle, 2004) whereas pollution (Ros- mesh size of about 1mm and they were identified with the enberg and Resh, 1993) or habitat fragmentation (Zwick, help of various taxonomical literatures. Table 1 shows the de- 1992) are the major causes in the temperate areas. scriptions of these sites. List of mayfly taxa of Palni and Car- Numerous investigations have been made in recent years on damom hills is given in the Table 2 and 3 respectively. the effect of climate change on mayflies. Clearly, climate Measuring Physicochemical Parameters changes are affecting the behavior and ultimately the ecology of some mayflies, for example, small increases in temperature Water samples were collected from sampling sites and vari- (3°C) over the short term cause early emergence of mayflies ous physicochemical parameters like pH, dissolved oxygen, (McKee and Atkinson, 2000). Climate changes alter precipi- air temperature, water temperature, water current, width of tation pattern, leading to greater flood magnitude and fre- the stream, hardness, alkalinity, total dissolved solids, con- quency in certain rivers. This results in changes in ecological ductivity and Biological oxygen demand were analyzed using structure and function, and loss of diversity through too fre- APHA guidelines (2005). quent scouring. With the continuing trend of temperature in- Statistical Analysis crease, the proportion of glacial melt and snow melt waters will change and lead to drastic changes in macroinvertebrate To view the trend of distribution of the stations based on en- communities, including mayflies. vironmental parameters the PCA (Principal Components Analysis) was used. PCA was calculated by using PAST soft- Ephemeroptera have been extensively used as bioindicators ware 4.02 (Hammer et al., 2001). Mathematically, PCA con- in aquatic biomonitoring programs (Srinivasan et al., 2019), sists of Eigen-analysis of a covariance or correlation matrix in biomarker studies and in ecotoxicological studies. During calculated on the original measurement data. To investigate the last two decades, EPT concept has successfully empha- the relationships between ecological factors and various sta- sized the significance of Ephemeroptera, Plecoptera, and Tri- tions, PCA was used. Canonical Correspondence Analysis choptera in describing environmental conditions (Lenat and (CCA) was made to found the community structure of may- Barbour, 1994). In the current investigation, we utilize multi- flies in relationship to environmental variables. variate examination strategy Canonical Correspondence

Aquat Res 4(1), 21-37 (2021) • https://doi.org/10.3153/AR21003 Research Article

Table 1. Details of the 30 study sites S. Name of Abbreviation Abbreviation Stream Altitude Latitude Longitude No the study site in PCA in CCA order (m) (N°) (E°) 1 Oothu Ooth P-1 3 1300 10º12' 77º26' 2 Perumalmalai Peru P-2 2 1400 10º18' 77º33' 3 Kurusadai Kuru P-3 2 1700 10º20' 77º28' 4 Ghandhi nagar Gand P-4 2 1600 10º18' 77º27' 5 Silver cascade Silv P-5 2 1700 10º12' 77º28' 6 Vattakanal Vatt P-6 2 1000 10º11' 77º25' 7 Fairy falls Fair P-7 3 290 10º13' 77º27' 8 Bear Shola falls Bear P-8 2 300 10º14' 77º27' 9 Fern hill falls Fern P-9 3 122 10º12' 77º20' 10 Pillar rock Pill P-10 1 2250 10º17' 77º28' 11 Near pillar rock Near pill P-11 1 2255 10º12' 77º30' 12 Pambar stream Pamb P-12 2 2248 10º13' 77º28' 13 Dhobikana Dhob P-13 3 2075 10º24' 77º24' 14 GundarFalls Gund P-14 2 2200 10º14' 77º26' 15 Poomparai Poom P-15 2 2133 10º13' 78º16' 16 Kounchi Kouc P-16 2 2360 10º29' 77º30' 17 Kurangani up Kura-up C-1 2 2410 11º00' 77º50' 18 Kurangani down Kura-down C-2 2 2345 11º00' 77º45' 19 B. L. Rave B.L.Rave C-3 1 1250 10º11' 77º25' 20 Poonthampanai Poon C-4 1 1300 11º12' 77º26' 21 Santhamparai near bridge San-bridge C-5 2 1350 11º00' 77º52' 22 Santhamparai near SDA school San-SDA C-6 4 1400 11º13' 77º28' 23 Mattupetty Dam stream Matt C-7 2 1700 11º16' 77º29' 24 Anayirankal stream Anai C-8 2 1950 11º18' 77º31' 25 Aranmanaiparai Aran C-9 3 2050 11º21' 77º33' 26 Popparai Popp C-10 4 1785 11º44' 77º26' 27 Bodimettu Bodi C-11 2 1500 11º15' 77º24' 28 Thoovanam falls Thuv C-12 3 1550 11º15' 77º15' 29 Nayamakkadu falls Naya C-13 2 2197 11º20' 77º10' 30 Chinnakanal falls Chin C-14 1 1800 11º27' 77º30'

Aquat Res 4(1), 21-37 (2021) • https://doi.org/10.3153/AR21003 Research Article

Table 2. Species of Mayflies in Palni hills ORDER FAMILY GENUS AND SPECIES 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Ooth Peru Kuru Gand Silv Vatt Fair Bear Fern Pill Near pill Pamb Dhob Gund Poom Koun Baetidae Baetis acceptus 11 12 8 31 11 19 22 19 27 17 11 17 17 24 30 17 Baetis conservatus 8 17 11 11 8 21 18 11 17 20 23 22 18 26 19 32 Tenuibaetis frequentus 12 21 22 8 17 43 52 29 29 33 42 32 20 42 17 42 Baetis ordinates 8 11 5 0 0 0 14 5 10 5 10 19 10 27 42 12 Labiobaetis geminatus 5 7 11 11 17 45 29 28 17 7 5 8 0 42 29 32 Ephemeroptera Centroptella similis 12 11 20 21 17 46 23 17 12 11 0 21 0 0 17 14 Centroptella ceylonensis 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Acentrella vera 0 0 0 0 0 0 0 0 0 0 0 0 12 11 0 11 Heptageniidae Afronurus sp. 26 0 0 22 0 0 0 0 0 0 0 0 34 41 0 0 Afronurus kumbakkaraiensis 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Epeorus petersi 0 0 0 0 0 0 0 0 0 10 0 0 0 26 0 0 Thalerosphyrus flowersi 0 0 0 0 0 0 0 0 0 0 0 0 0 0 33 0 Leptophlebiidae Choroterpes alagarensis 22 18 0 47 41 39 52 37 23 47 32 38 65 27 0 35 Edmundsula lotica 0 0 17 10 0 33 29 27 15 53 62 31 24 17 17 33 Indialis badia 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 13 Isca purpurea 24 19 21 25 41 43 21 26 37 27 18 23 36 28 0 39 Nathanella indica 10 5 17 0 0 0 19 22 27 0 5 11 0 0 0 0 Notophlebia jobi 5 0 11 0 23 16 6 17 17 7 0 23 0 0 21 0 Petersula courtallensis 15 0 0 20 17 18 14 10 18 11 11 10 17 14 17 0 Neoephemeridae Potamanthellus ganges 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 Thraulus gopalani 0 0 6 4 0 8 5 9 0 0 13 21 0 0 21 0 Teloganodidae Teloganodes dentata 11 8 17 14 17 11 8 21 14 24 19 12 19 0 32 32 Teloganodes kodai 17 14 8 27 14 21 22 23 33 16 62 42 0 0 27 28 Teloganodes insignis 13 6 15 8 19 0 0 0 0 14 5 45 52 38 54 0 Ephemeridae Ephemera nadinae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 52 Caenidae Caenis sp. 32 14 8 10 27 12 21 32 29 13 18 7 8 12 29 36

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Table 3. Species of Mayflies in Cardamom hills ORDER FAMILY GENUS AND SPECIES 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Kura-up Kura- down B.L.Rave Poon San-bridge San-SDA Matt Anai Aran Popp Bodi Thuv Naya Chin Baetidae Baetis acceptus 0 0 17 17 0 0 0 42 0 0 22 0 41 12 Baetis conservatus 0 0 11 15 0 0 0 31 0 19 0 12 29 32 Tenuibaetis frequentus 42 21 29 42 13 21 32 31 17 23 33 27 17 27 Baetis ordinatus 0 0 33 27 31 17 17 21 22 17 22 18 23 30 Labiobaetis geminatus 32 17 21 41 0 39 32 42 17 10 17 27 37 41 Ephemeroptera Centroptella similis 37 21 17 31 34 13 33 27 0 15 16 22 0 30 Centroptella ceylonensis 0 0 16 34 5 25 29 0 11 0 0 0 17 0 Acentrella vera 0 0 25 0 0 30 31 0 0 21 32 0 0 0 Heptageniidae Afronurus sp. 0 0 0 32 0 0 33 24 29 42 0 33 32 25 Afronurus kumbakkaraiensis 37 17 42 42 15 19 47 37 33 32 21 37 29 33 Epeorus petersi 31 20 33 27 23 22 31 33 12 42 32 33 37 12 Thalerosphyrus flowersi 47 28 0 0 0 0 0 0 0 33 14 0 0 0 Leptophlebiidae Choroterpes alagarensis 62 32 52 21 33 41 21 35 27 55 32 41 24 32 Edmundsula lotica 0 0 0 0 16 17 31 0 31 32 37 33 23 27 Indialis badia 23 32 0 0 0 0 0 29 0 0 0 0 0 0 Isca purpurea 5 0 15 33 21 55 36 44 32 17 13 31 21 30 Nathanella indica 32 17 0 0 0 28 0 0 0 0 0 0 0 21 Notophlebia jobi 13 11 27 13 14 10 19 0 35 27 20 27 30 21 Petersula courtallensis 10 15 0 0 0 0 23 27 34 32 15 13 11 0 Neoephimeridae Potamanthellus ganges 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Thraulus gopalani 17 11 0 0 0 0 0 0 25 0 0 0 5 0 Teloganodidae Teloganodes dentata 0 0 0 27 21 18 0 16 20 19 27 0 27 23 Teloganodes kodai 0 0 0 0 23 21 43 0 34 0 14 17 10 0 Teloganodes insignis 0 0 0 0 17 17 0 0 25 0 0 0 0 0 Ephemeridae Ephemera nadinae 98 5 0 0 0 0 0 0 0 0 0 0 0 0 Caenidae Caenis sp. 27 42 42 33 17 29 21 32 19 31 0 23 39 31

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Results and Discussion Dhobikana and Poomparai are distantly placed. Component 3 (Figure 4) includes Silvercascade, Kounchi, Pillar rock, near PCA Analysis of Palni Hills pillar rock, Fern hill, Gundar and Ghandhinagar. Here pH, Based on the scree plot results, three components were cho- water temperature, air temperature, conductivity, width and sen in both Palni and Cardamom hills. PCA of Palni hills TDS are highly positively correlated whereas DO, velocity, identified three principle components of water quality hardness, alkalinity and BOD are negatively correlated. Fern measures that explained 80.05% of the variation (Table 4) in hill is placed away from other sites. water quality between streams. Figure 1 shows the PCA of Table 4. Variance explained and the eigen val- Palni hills. PCA analysis of Palni hills categorize the sites ues for the physico-chemical variables into three groups which are referred as components namely of Palni hills component 1, component 2 and component 3. Axis Eigen value % Variance Component 1 is positively correlated with the parameters like 1 2.94849 26.804 water temperature, air temperature and dissolved oxygen (DO), velocity and width of the stream (Figure 2), pH and 2 2.5278 22.98 hardness are not supporting these sites. The sites included in 3 1.86774 16.979 this component are Oothu, Fairy falls, Vattakanal, Perum- 4 1.23612 11.237 almalai, Kurusadai and Bear chola. In this component Perum- 5 0.904433 8.2221 almalai is distantly placed. 6 0.722309 6.5664 The study sites in component 2 are Dhobikana, Poomparai 7 0.422977 3.8452 and Pambar are highly correlated with Hardness, alkalinity, 8 0.210023 1.9093 water temperature, air temperature and width of the stream 9 0.088112 0.80101 (Figure 3). pH, conductivity, DO and BOD are negatively correlated with the component 2 sites. In this component, 10 0.069933 0.63575 11 0.002067 0.018794

3.6 Dhop 3 Poom-p 2.4 Alkalinity Pamp 1.8 PCA 2 Peru Hardness 1.2 velocity Wi 0.6 Water tempFair Air temp Ooth -3 -2.4 -1.8 -1.2 -0.6 TDS0.6 Be 1.2 1.8 2.4 pH DO Pill -0.6 Kuru Vatt Silv Kouc -1.2 Fern Gund Gand BOD Pitn -1.8 Conductivity PCA 1

Figure 1. Principal component Analysis for Palni hills

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0.9279 0.8 0.8 0.7239 0.6 0.6061 0.4 0.312 0.2 0.1519 0.1358 0.06577 0 0.01461 Correlation -0.2

-0.4

-0.6 -0.5657

-0.8 -0.8512 pH DO TDS BOD Width Alkalini velocity Air_temp Conducti Hardness Watertem Figure 2. Component 1 of PCA in Palni hills

0.8 0.8785

0.6 0.5981 0.4

0.2 0.2457 0.2391 0.1144 0 0.05851 -0.003829

-0.2Correlation -0.1288-0.163

-0.4

-0.6 -0.6474 -0.8 -0.8144 pH DO TDS BOD Width Alkalini velocity Air_temp Conducti Hardness Watertem Figure 3. Component 2 of PCA in Palni hills

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0.708 0.64 0.6516 0.48 0.4558 0.32 0.2777 0.16 0.2079 0.1934

Correlation -0.065 -0.08308 -0.07149 -0.16 -0.1073

-0.32

-0.48

-0.64 -0.674 pH DO TDS BOD Width Alkalini velocity Air_temp Conducti Hardness Watertem

Figure 4. Component 3 of PCA in Palni hills

PCA Analysis of Cardamom Hills PCA for Cardamom hill is shown in Figure 5. The first three Table 5. Variance explained and the eigenvalues for components of the PCA for physicochemical parameters at the physico-chemical variables of Carda- the sites collectively explained 77% of the variability at these mom hills sites (Table 5). Axis Eigen value % Variance In component 1 (Figure 6) DO, air temperature, water tem- 1 3.58035 32.549 perature, hardness, alkalinity, TDS, conductivity and BOD 2 2.38903 21.718 are positively correlated with the sites Popparai, Poontham- panai, Bodimettu, Anayirangal, Chinnakanal, Aranmanai- 3 1.77327 16.121 parai and Mattupatti. But these sites are negatively correlated 4 1.06369 9.6699 with pH, velocity and width of the stream. Supporting factors 5 0.880061 8.0006 of component 2 (Figure 7) are pH, velocity, width of the 6 0.468153 4.2559 stream, hardness, BOD and alkalinity. Air temperature, water 7 0.416393 3.7854 temperature, DO, TDS and conductivity are negatively corre- 8 0.222051 2.0186 lated to the site Nayamakkadu. Nayamakkadu alone is placed under component 2. 9 0.118548 1.0777 10 0.062119 0.56472 Figure 8 representing component 3 shows that all the param- 11 0.026342 0.23947 eters are highly positively correlated with the sites. The sites included in this component are Kurangani up, Kurangani down, Thoovanam, B. L. Rave, Santhamparai SDA and San- thamparai near bridge. The site Santhamparai near bridge is plotted far away in the third components.

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Naya 2.4 Poom-c Velocity Popp 1.6 Hardness Chin Alkalinity Aran 0.8 BOD Width pH Thid Bott Anai -3 -2.4 -1.8 -1.2 -0.6 0.6 1.2 1.8 2.4 PCA2 Thuv Conductivity Kur-down Kur-up B.L.Ra -0.8 AirTemp TDS Watertemp Matt San-SDA -1.6 DO -2.4

-3.2 San-bri

-4 PCA 1

Figure 5. Principal component Analysis for Cardamom hills

0.8 0.8237 0.7295 0.6 0.6389 0.6297

0.4 0.3256 0.2 0.2311 0.238 0.113 0 Correlation -0.2 -0.2152

-0.4 -0.3501

-0.6

-0.8 -0.7317 pH DO TDS Width BOD_ Alkalini velocity AirTemp Conducti Hardness Watertem Figure 6. Component 1 of PCA in Cardamom hills

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0.8 0.7207 0.6 0.6315 0.5545 0.4 0.3816 0.2

0 0.03407 0.06471 -0.04711

Correlation -0.2

-0.3157 -0.4 -0.423 -0.4781 -0.6

-0.8 -0.8012 pH DO TDS Width BOD_ Alkalini velocity AirTemp Conducti Hardness Watertem Figure 7. Component 2 of PCA in Cardamom hills

0.9

0.8 0.8131

0.7

0.6 0.6358 0.5953 0.5 0.4719 0.4

Correlation 0.3 0.3429 0.2559 0.2 0.1786 0.1 0.07416 0.07015 0 -0.0053020.0001558 -0.1 pH DO TDS Width BOD_ Alkalini velocity AirTemp Conducti Hardness Watertem

Figure 8. Component 3 of PCA in Cardamom hills

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pH present study TDS is highly correlated with all the components. Mayfly nymphs are sensitive to low pH. In Palni hills components 1 and 2 are negatively correlated with pH whereas, Hardness component three is positively correlated. The pH of the sites Total hardness is used to describe the effect of dissolved min- ranges between 6.3-7.52 (Table 6). Due to anthropogenic im- erals (mostly Ca and Mg). Optimal values of hardness of pacts, the pH is slightly acidic in certain sites like Vattakanal. aquatic life range from 100 to 200 mg/L. At levels above 250 Streams typically have a slightly basic pH value ranging from mg/L, calcium carbonate will begin to precipitate. According 7 to 8. Most organisms have optimal pH ranges in which they to the results, hardness is negatively correlated with compo- live that fall between 6 and 8 (Campbell and Wildberger, nents 1 and 3 in Palni hills, and in Cardamom hills it is posi- 2001). Even slight changes in the normal pH can have con- tively correlated with all the sites. The high value of total siderable effects on mayflies. In cardamom hills except com- hardness may be due to discharge of sewage from nearby ponent 1 the other two components are negatively correlated places, use of soaps and detergents by laundries, washing, with pH. In this hill the pH ranges 6.0 to 7.4 (Table 7). bathing by people. Dissolved Oxygen Biological Oxygen Demand (BOD) The standard levels indicate that Dissolved Oxygen (DO) 4 – Healthy streams which have BOD reading of less than 2 mg/l, 7 mg/l is good for mayflies (Payne, 1986). DO plays a vital whereas polluted streams is of 10 mg/L. In components 2 and role in supporting aquatic life and is susceptible to slight en- 3 in Palni hills, the BOD is negatively correlated and the other vironment changes and hence DO have been extensively used components are positively correlated. as a parameter delineating water quality and to evaluate the degree of freshness of a river (Fakayode, 2005). DO is posi- Conductivity tively correlated with component 1 of Palni and Components Most streams ranges between 50 to 1500 µS/cm. Ideal levels 1 and 3 are positively correlated in Cardamom hills. The DO of conductivity for the mayfly richness ranges 150 to 500 in the sites was found within the range (4 -7.7 mg/L) (Table µS/cm. In the study sites, components 2 of both the hills are 6). negatively correlated. Water Temperature and Air Temperature Velocity and Stream Width Based on the earlier works it is understood that the positive Velocity is correlated positively except component 3 for Palni correlation with the water temperature and air temperature hills and component 1 of Cardamom hills. Stream width is plays a major role in maintaining the number of organisms. positively correlated except component 1 of Palni hills. The PCA results of both the hills show positive correlation for Water temperature and air temperature except component CCA Analysis 2 in cardamom hills. The relationship between the mayfly’s communities and the Alkalinity environmental parameters was depicted by CCA (Canonical Correspondence Analysis). For CCA analysis, eleven envi- Total alkalinity of water is due to presence of mineral salt ronmental variables were used. Figure 9 shows the result of present in it. It is primarily caused by the carbonate and bi- ordination of sites and Ephemeroptera with respect to envi- carbonate ions. Levels of alkalinity between 100 and 200 ronmental variables in Palni hills. From the outcomes, the mg/L provide ideal buffering within a stream. But it has the destinations P-1, P-4, P-11, P-13, P-14 and P-16 were found permissible limit up to 600mg/L. In the present study the al- away from the referenced ecological factors and were influ- kalinity falls under the permissible limit (345-367 mg/L). enced by anthropogenic action and slightly polluted. The sites Among both the hills alkalinity show positive relation with P-2, P-3, P-5, P-6 P-7, P-8, P-9 and P-10 were decidedly con- all components except Component 3 of Palni hills. nected with factors like air temperature, water temperature, Total Dissolved Solids (TDS) DO, BOD, TDS, conductivity and current speed whereas it is it is contrarily related with pH, altitude, hardness and alkalin- Total Dissolved Solid is a measurement of inorganic salts, or- ity. Sites include P-12 and P-15 were positively correlated ganic matter and other dissolved materials in water, TDS with pH, altitude, hardness and alkalinity and adversely re- above 1340 mg/l may adversely affect mayflies (Good fellow lated with air temperature, water temperature, DO, BOD, et al., 2000; SETAC, 2004). TDS and the associated elevated TDS, current speed and conductivity. conductivity seem to be particularly toxic and stressor to mayfly community in the streams (Pond et al., 2008). In the

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Table 6. Physico-chemical features, water quality parameters of the sampling sites in Palni hills D.O Air temp Water temp Current speed Width Hardness Alkalinity Total dissolved Conductivity BOD S. No Site pH (mg/L) (ºC) (ºC) (sec m-1) (m) (mg/L) (mg/L) solids (ppt) (µs/cm) (mg/L) 1 Ooth 6.8 4.6 18.7 15 11 6 – 7 73 342 0.132 108 2.3 2 Peru 6.3 4.7 18.3 15.4 11 2 – 3 87 342 0.099 79 2.45 3 Kuru 7.3 4.2 17.7 16 6 2.5 – 3 83 312 0.089 87 3.88 4 Gand 7.35 4.3 16 14 5 2 – 3 90 288 0.093 112 2.65 5 Silv 7.36 4.2 15.7 13.4 3 5 – 10 98 299 0.084 103 2.34 6 Vatt 6.3 4.9 18.3 14 5 1 – 2 85 321 0.079 102 2.53 7 Fair 6.5 4.4 19.7 16.1 9 1 – 2 94 314 0.083 97 2.78 8 Bear 7.1 4 18.9 15 6 2 – 3 85 323 0.769 110 2.57 9 Fern 6.5 4.8 19 14.6 8 1 – 2 102 312 0.094 125 4.12 10 Pill 7.47 4.4 15 11.4 6 0.5 – 1 90 343 0.122 105 3.23 11 Near pill 7.4 4.5 15.4 10 6 1 – 2 92 288 0.093 112 2.65 12 Pamb 6.9 4.3 15.8 13.2 5 2 – 3 112 345 0.098 93 1.3 13 Dhob 7.52 4 16.3 14.1 6 1 – 2 156 367 0.085 76 2.32 14 Gund 7.45 4 14.5 13 4 4 – 6 107 304 0.097 126 2.87 15 Poom 7.25 4.3 15.4 12 5 2 – 3 143 353 0.112 88 1.4 16 Kouc 7.3 4.4 14 10.5 4 0.25–0 .5 94 314 0.083 97 2.78 Table 7. Physico-chemical features, water quality parameters of the sampling sites in Cardamom hills D.O Air Temp Water temp Current speed Width Hardness Alkalinity Total dissolved Conductivity BOD S. No Site Ph (mg/L) (ºC) (ºC) (sec m-1) (m) (mg/L) (mg/L) solids (ppt) (µs/cm) (mg/L) 1 Kura-up 6 6.7 21 18.5 3 – 4 10 72 312 0.077 80 1.74 2 Kura-down 7.3 6.4 22 18.4 4 – 5 11 82 267 0.089 79 1.32 3 B.L.Rave 7.2 6.3 23 19.1 4 – 6 8 48 333 0.082 92 0.89 4 Poon 7.4 6 22 20.2 3 – 4 10 94 384 0.132 108 2.3 5 San-bridge 6.5 7.7 23 18.3 2 – 3 5 87 267 0.688 124 1.65 7 San-SDA 7.4 6.8 23 20.2 4 – 5 11 55 237 0.073 86 1.54 6 Matt 6.4 7.4 24 19.1 3 – 4 4 89 306 0.129 105 2.65 8 Anai 7.1 7.4 24 20.3 3 – 4 8 173 435 0.1 89 3.46 9 Aran 6.5 6 23 16.5 4 – 6 7 102 354 0.093 106 2.32 10 Popp 7.5 5.2 23 18.4 5 – 6 12 156 345 0.098 105 4.32 11 Bodi 6.4 6.5 20 19.4 4 – 5 4 98 299 0.084 103 2.76 12 Thuv 6.4 6.8 22 17.1 3 – 4 10 61 321 0.043 79 1.32 13 Naya 6.8 4.1 21 16.4 4 – 5 8 143 342 0.098 93 1.3 14 Chin 6 6.3 22 18.3 5 – 6 3 156 345 0.096 106 4.35

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Labiobaetis geminatus, A ker- Afronurus sp., A kum- Af- The taxa like B con- Baetis conservatus, B ord- Baetis ordi- ronurus kumbakkaraiensis, Ep pet- Epeorus petersi, P cour- natus, Ac ver- Acentrella vera, T flo- Thalerosphyrus flow- Petersula courtallensis, Po gan- Potamanthellus ganges and ersi, C ala- Choroterpes alagarensis, Ed lot- Edmundsula lo- Te den- Teloganodes dentata were sensitive to low BOD, pH, tica, Ind bad- Indialis badia, Po gan- Potamanthellus ganges, alkalinity and hardness and sensitive to high DO. It shows Th gop- Thraulus gopalani, Te ins- Teloganodes insignis that Baetis genera are tolerant to acidic and alkaline environ- gets upheld by environmental attributes like pH, altitude, ment. Taxa such as Ce cey- Centroptella ceylonensis, Ac ver- hardness and alkalinity and negatively correlated with air Acentrella vera, Ed lot- Edmundsula lotica, I pur- Isca pur- temperature, water temperature, DO, BOD, TDS, conductiv- purea, No jo- Notophlebia jobi, Te kod- Teloganodes kodai ity and current speed. If riparian vegetation is high, there is and Te ins- Teloganodes insignis shows sensitivity to low an increase of pH in natural water (Wetzel, 2001). So the out- levels of TDS, conductivity and air temperature and shows comes appears, the above taxa lean toward denser riparian sensitivity to high levels of water temperature, current speed environment for their source of living..Te fre- Tenuibaetis and altitude. Te fre- Tenuibaetis frequentus and Cae sp- Cae- frequentus, Lb ger- Labiobaetis geminatus, Ce sim- Centrop- nis sp shows sensitivity to high levels of TDS, conductivity tella similis, Ce cey- Centroptella ceylonensis, A kum- Af- and air temperature and shows less sensitivity to high levels ronurus kumbakkaraiensis, C ala- Choroterpes alagarensis, of water temperature, whereas Ind bad- Indialis badia shows I pur- Isca purpurea, N ind- Nathanella indica, No jo- No- less sensitivity to altitude and current speed tophlebia jobi, Cae sp- Caenis sp gets enriched by the attributes like air temperature, water temperature, DO, BOD, TDS, Site C-1, which is not delicate to any of the eleven ecological conductivity and current speed and diminished by the factors factors, and Ephemera nadinae, which additionally shows no pH, altitude, hardness and alkalinity. They don't lean toward relationship or availability with any of the variable. The CCA low temperature and low dissolved oxygen, so above refer- results of both Palni and Cardamom hills substantiates that ence taxa just incline toward cool condition and they are the the distribution and community structure of Ephemera nadi- markers of natural contamination since they are profoundly nae is mysterious and still needs further more investigation tolerant to the acidic and basic situations. B acc- Baetis ac- of overwhelming metals and other environmental properties. ceptus, A ker- Afronurus sp., Ep pet- Epeorus petersi, P cour- Baetis and Tenuibaetis both shows distinctive community Petersula courtallensis, Te den- Teloganodes dentata, Te structure pattern, though they both originates from a single kod- Teloganodes kodai and Eph nad- Ephemera nadinae ancestor. Gencer Turkmen and Ozkan (2011) and Gencer shows no relation to any of the above 11 environmental vari- Turkmen and Nilgun Kazanci (2020) suggests that Baetis ables. milani is β-mesosaprobic, our results also substantiates with that as Baetis species are sensitive to high DO and it prefers The ordination diagram of CCA (Figure 10) displays the sites β-mesosaprobic habitat. According Caenis sp. in both Palni of Cardamom hills with species of Ephemeroptera and envi- and Cardamom hills prefers different habitats and it proves ronmental variables. They display variation in species com- that more Caenis species complex were present in Palni and position over the sites. From the results, sites C-3, C-4, C-8, Cardamom hills. The outcome likewise demonstrates Indialis C-10, C-13 and C-14 shows positive correlation with BOD, badia diversity and distribution were more in high altitudinal pH, alkalinity and hardness and shows negative correlation area. From the results, it is apparent that Centroptella similis with DO. Sites C-5, C-6, C-7, C-9, C-11 and C-12 shows pos- prefer oligosaprobic environment. itive correlation with TDS, conductivity and air temperature and negatively correlated with water temperature, current It was noticed that locales Poomparai, Dhobikana, Kounchi speed and altitude. Site 2 shows negative correlation with of Palni hills and Kurangani up and down of Cardamom hills ecological attributes like TDS, conductivity and air tempera- are plotted away from all the variables and the only reason ture and shows positive correlation with water temperature, that can be suggested is human impedance (i.e. Anthropo- altitude and current speed. genic impacts). Ce sim- Centroptella similis, T flo- Thalerosphyrus flowersi, N ind- Nathanella indica, P cour- Petersula courtallensis and Th gop- Thraulus gopalani were sensitive to low amount of DO and delicate to high discharge of BOD, pH, alkalinity and hardness. It proves the above reference organisms are good indictaors of water quality because they are highly sensitive to acidic, alkaline environment. B acc- Baetis acceptus, B con- Baetis conservatus, B ord- Baetis ordinatus, Lb ger-

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(B acc- Baetis acceptus, B con- Baetis conservatus, Te fre- Tenuibaetis frequentus, B ord- Baetis ordinatus, Lb ger- Labiobaetis geminatus, Ce sim- Centroptella similis, Ce cey- Centroptella ceylonensis, Ac ver- Acentrella vera, A ker- Afronurus sp, A kum-Afronurus kumbakkaraiensis , Ep pet- Epeorus petersi, T flo- Thalerosphyrus flowersi, C ala- Choroterpes alagarensis, Ed lot- Edmundsula lotica, Ind bad- Indialis badia, I pur- Isca purpurea, N ind- Nathanella indica, No jo- Notophlebia jobi, P cour- Petersula courtallensis, Po gan- Pota- manthellus ganges, Th gop- Thraulus gopalani, Te den- Teloganodes dentata, Te kod- Teloganodes kodai, Te ins- Teloganodes insignis, Eph nad- Ephemera nadinae, Cae sp- Caenis sp.) Figure 9. Canonical Correlation Analysis of Palni hills

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(B acc- Baetis acceptus, B con- Baetis conservatus, Te fre- Tenuibaetis frequentus, B ord- Baetis ordinatus, Lb ger- Labiobaetis geminatus, Ce sim- Centroptella similis, Ce cey- Centroptella ceylonensis, Ac ver- Acentrella vera, A ker- Afronurus sp., A kum- Afronurus kumbakkaraiensis , Ep pet- Epeorus petersi, T flo- Thalerosphyrus flowersi, C ala- Choroterpes alagarensis, Ed lot- Edmundsula lotica, Ind bad- Indialis badia, I pur- Isca purpurea, N ind- Nathanella indica, No jo- Notophlebia jobi, P cour- Petersula courtallensis, Po gan- Pota- manthellus ganges, Th gop- Thraulus gopalani, Te den- Teloganodes dentata, Te kod- Teloganodes kodai, Te ins- Teloganodes insignis, Eph nad- Ephemera nadinae, Cae sp- Caenis sp.) Figure 10. Canonical Correlation Analysis of cardamom hills

Conclusions Based on PCA results, it tends to be reasoned that the sites in not supported by physicochemical parameters, mainly due to Palni hills, which are plotted far apart like Dhobikana, Fern pollution. However, Ephemeroptera were sensitive to water hill and Poomparai, are not supported by the physico-chemi- quality changes specially to DO, pH, conductivity and hard- cal parameters like the other sites in Palni hills. This is abso- ness their number is less in these stations compare with other lutely a direct result of anthropogenic activity, because Fern stations. From the CCA results, it is found that Baetis species hill and Poomparai are excursion spots where human obstruc- lean towards β-mesosaprobic habitat and Indialis badia fa- tion is more in these streams. Whereas Dhobikana is a place vors high altitudinal area. Sites like Poomparai, Dhobikana, where dhobis are involved in washing clothes so detergent Kounchi of Palni hills and Kurangani up and down of Carda- pollution is more there. In cardamom, hills Santhamparai near mom hills are plotted away from all the environmental varia- bridge and Nayamakkadu are left far apart indicating they are bles.

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In this work, it is discovered that not all physicochemical pa- Fakayode, S.O. (2005). Impact of industrial effluents on wa- rameters are emphatically or adversely corresponded. But it ter quality of the receiving Alaro River in Ibadan, Nigeria, is understood that pH, dissolved oxygen, BOD, hardness and African Journal of Environmental Assessment and Manage- alkalinity were the crucial factors. This agrees with numerous ment, 10, 1-13. investigations that have been done previously (Steinman et al., 2003). Dissolved oxygen is the key to the abundance of Goodfellow, W.L., Ausley, L.W., Burton, D.T., Denton, Ephemeroptera as oxygen is the significant component to all D.L., Dorn, P.B., Grothe, D.R., Heber, M.A., Norberg living creature to remain alive and slight changes on the pH King, T.J., Rodgers, J.H. Jr. (2000). Major ion toxicity in likewise change the presence of Ephemeroptera. effluents: a review with permitting recommendations. Envi- ronmental Toxicology and Chemistry, 19, 175-182. Compliance with Ethical Standard https://doi.org/10.1002/etc.5620190121

Conflict of interests: The authors declare that for this article they Hammer, O., Harper, D.A.T., Ryan, P.D. (2001). PAST have no actual, potential or perceived conflict of interests. (Paleontological Statistics software package for education Ethics committee approval: This study was conducted in accord- and data analysis). Palaeontologia Electronica, 4(1), 9. ance with ethics committee procedures of animal experiments. Funding disclosure: - Kazanci, N., Türkmen, G., Ekingen, P., Basoren, O. (2017). Evaluation of Plecoptera (Insecta) community com- Acknowledgments: - position using multivariate technics in a biodiversity hotspot. Disclosure: - International Journal of Environmental Science and Tech- nology, 14, 1307-1316. https://doi.org/10.1007/s13762-017-1245-y References APHA (American Public Health Association) (2005). Lenat, D.R., Barbour, M.T. (1994). Using benthic macroin- Standard methods for the examination of water and vertebrate community structure for rapid, cost-effective, wa- wastewater, 21st Edition, Washington D.C. ISBN: ter quality monitoring: rapid bioassessment.Biological moni- 9780875530475 toring of aquatic systems, Lewis Publishers, Boca Raton, Florida, pp. 187-215. BarberJames, H.M., Gattolliat, J.L, Sartori, M., Hub- bard, M.D. (2008). Global diversity of mayflies (Ephemer- McKee, D., Atkinson, D. (2000). The influence of climate optera: Insecta) in freshwater. Hydrobiologia, 595, 339-350. change scenarios on populations of the mayfly Cloeon dip- https://dx.doi.org/10.1007/s10750-007-9028-y terum. Hydrobiologia, 441, 55-62. https://doi.org/10.1023/A:1017595223819 Benstead, J.P., Pringle, C.M. (2004). Deforestation alters there source base and biomass of endemic stream insects in Myers, N., Mittermeier, R.A., Mittermeier, C.G., Da eastern Madagascar. Freshwater Biology, 49, 490–501. Fonseca, G.A., Kent, J. (2000). Biodiversity hotspots for https://doi.org/10.1111/j.1365-2427.2004.01203.x conservation priorities. Nature, 403(6772), 853. https://doi.org/10.1038/35002501 Burton, T.M., Sivaramakrishnan, K.G. (1993). Composi- tion of the insect community in the streams of the silent val- Payne, A.L. (1986). The ecology of tropical lakes and riv- ley National Park in South India. Journal of Tropical ecol- ers. Londres: John Wiley & Sons. pp. 327-328. ISBN: 0‐ ogy, 34, 1-16. 471‐90524‐0

Campbell, G., Wildberger, S. (2001). The monitor’s hand- Pond, G.J., Passmore, M.E., Borsuk, F.A., Reynolds, L., book. A Reference Guide for Natural Water Monitoring, Rose, C.J. (2008). Downstream effects of mountaintop coal LaMotte Company, Chestertown, Maryland, USA, 6 p. mining: Comparing biological conditions using family- and genus- level macroinvertebrate bioassessment tools. Journal Duran, M., Akyildiz, G.K. (2011). Evaluating benthic ma- of the North American Benthological Society, 27, 717-737. croinvertebrate fauna and water quality of Suleymanli Lake https://doi.org/10.1899/08-015.1 (Buldan-Denizli) in Turkey. Acta Zoologica Bulgarica, 63(2), 169-178.

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Rosenberg, D.M., Resh, V.H. (1993). Freshwater biomoni- Türkmen, G., Kazanci N. (2020). Community Structure of toring and benthic macroinvertebrates. Chapman & Hall, Mayflies (Insecta: Ephemeroptera) in a Biodiversity Hotspot New York. pp. 1-9. ISBN: 0412 02251 6 as Revealed by Multivariate Analyses. Acta Zoologica Bul- garica, 72(1), 67-81. SETAC (Society of Toxicology and Chemistry) (2004). Technical issue paper: Whole effluent toxicity testing: ion Türkmen, G., Ozkan, N. (2011). Larval Ephemeroptera rec- imbalance. Pensacola, FL, USA, 4 p. ords from Marmara Island and Kapıdağ Peninsula (North- Western Turkey) with new record of Baetis milani Godunko, Srinivasan, P., Sivaruban, T., Isack, R., Barathy, S. Prokopov & Soldan 2004. Review of Hydrobiology, 4(2), 99- (2019). Bio-monitoring and detection of water quality using 113. Ephemeroptera, Plecoptera and Trichoptera (EPT) complex in Karanthamalai Stream of Eastern Ghats. Indian Journal of Wetzel, R.G. (2001). Limnology - Lake and river ecosystem, Ecology, 46(4), 818-822. 3rd edition, USA. https://doi.org/10.1672/0277- https://doi.org/10.1007/BF00731036 5212(2003)023[0877:IOCGAP]2.0.CO;2 Zwick, P. (1992). Stream habitat fragmentation - a threat to Steinman, A.D., Conklin, J., Bohlen, P.J., Uzarski, D.G. biodiversity. Biodiversity Conservation, 1, 80-97. (2003). Influence of cattle grazing and pasture land use on macroinvertebrate communities in freshwater wetlands. Wet- lands, 23, 877-889.

37 AQUATIC RESEARCH

E-ISSN 2618-6365

Aquat Res 4(1), 38-54 (2021) • https://doi.org/10.3153/AR21004 Research Article

The fishes of the Bolaman Stream, Northern Turkey

Serkan SAYGUN

Cite this article as: Saygun, S. (2021). The fishes of the Bolaman Stream, Northern Turkey. Aquatic Research, 4(1), 38-54. https://doi.org/10.3153/AR21004

Ordu University, Fatsa Faculty of Marine ABSTRACT Sciences, Department of Fisheries Technology Engineering, 52400 In this study, the fish species inhabiting the Bolaman Stream drains to the Black Sea from the Fatsa Fatsa- Ordu/Turkey coast (Ordu Province, Turkey) was reported for the first time. The study was caught out nonperiodically by sampling from seven stations in the Bolaman Stream between July 2017 and No- vember 2018. Fish samples were captured with an electroshock device. With this study, it was ORCID IDs of the author(s): determined that the fish fauna of the Bolaman Stream is represented by 10 species in five families S.S. 0000-0002-9789-3284 (Acheilognothidae, Cyprinidae, Gobiidae, Leuciscidae, and Salmonidae). These species were as follows, respectively Rhodeus amarus, Barbus tauricus, Capoeta banarescui, Neogobius fluviatilis, Ponticola turani, Alburnus derjugini, Squalius cephalus, Vimba vimba, Alburnoides fasciatus,

and Salmo coruhensis. Keywords: Fish fauna, Fish taxonomy, New record, Inland waters

Submitted: 22.06.2020 Revision requested: 06.09.2020 Last revision received: 15.07.2020 Accepted: 17.09.2020 Published online: 19.11.2020

Correspondence: Serkan SAYGUN E-mail: [email protected]

Available online at http://aquatres.scientificwebjournals.com

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Introduction Since three-quarters of the world constitute an aquatic habi- Material and Methods tat, there is a continuous rise as a result of increasing scientific studies in the species number of fish having the fifty per- The study was carried out by sampling nonperiodically fish centages of vertebrates. It was reported that this number has at seven sampling stations on the Bolaman Stream (Figure 1) been 35672 by adding new species within the last quarter of between July 2017 and November 2018 as specified in the 2020 (Fricke et al., 2020). In Turkey, the first ichthyo-faunis- examined material section below. The Bolaman Stream ini- tic study began in the first half of the nineteenth century by tially flows along the provincial borders of Tokat and Ordu sending twenty marine species collected from Trabzon Prov- in a westerly direction. Later, it turns north and passes ince to British researcher (Abbot, 1835). In the last 15 years, through the village of Zaferimilli in Ordu Province. It flows it has been observed that the number of fish detected has in- shortly afterward east past the city Aybastı. The Bolaman creased from 236 (Kuru, 2004) to 384 (Çiçek et al., 2020) in Stream then flows through the city Kabataş. Then the Gölköy Turkey. This number reached 391 with some recent addi- Stream flows from the right into the stream. In Eleşi Brook tional records by Çiçek (2020), Kaya et al. (2020a; 2020b), meets the stream from the left (Anonymous, 2018). Detailed and Kaya (2020). However, in another source, it was in- survey information (coordinates, altitudes, species, specimen formed that this species number reached only 401 in freshwa- quantity, and collection codes) of stations were listed in Table ters of Turkey (Froese and Pauly, 2019). Many studies in this 1. At least five fish samples from each species were collected area are still ongoing, and it is understood that Turkish inland quarterly with an electroshock device (SAMUS™-725MP). waters have a potential for new species that have not yet been After sampling, the fish specimens were firstly anesthetized discovered. By redefining previously discovered fish species, with oil of cloves and after stopping breath then stored within species confusion is also being tried to be eliminated. There a 4% formaldehyde solution in Fatsa Faculty of Marine Sci- are many small streams of various sizes such as the Kurna, ence (FFMS) of Ordu University (ODU) for species identifi- Tabakhane (Ünye), Çalış (Fatsa) Streams for, etc. in the cation. Later, the meristic characters dorsal (D), pectoral (P), Black Sea basin and have not been studied as ichthyofaunistic pelvic (V), and anal fin (A) ray numbers (spinous and yet. The Bolaman stream in Ordu Province was one of them, branched rays) with lateral line (LL) scale counting were also. made. Lateral line scales were counts from the anteriormost scale (the first one to touch the shoulder girdle) to posterior- The Bolaman is a stream to flow into the Black Sea in the most one (at the end of the hypural joint) (Stoumboudi et al., northern Turkish provinces of Ordu and Tokat. The stream 2006). Standard length (SL) was measured from the point of was called Sidenus in antiquity. The Bolaman Stream rises in the snout to the end of the hypural joint (Stoumboudi et al., the Canik Mountains, a mountain range of the Pontic Moun- 2006). Head length (HL) was measured from the anteriormost tains. The Bolaman stream continues its course to the north part of the head (jaws closed) to the posteriormost point of and pours into the Black Sea in the eastern of Fatsa (Anony- the opercular bone, excluding spines and gills membrane mous, 2018). (Holčík, 1989). In consider the other taxonomic studies conducted in a lake All the other morphometric characters changed from species and several rivers in around Ordu province, in which have to species were recorded in Microsoft Excel™ program by been Melet River, Ilıca and Yalıköy Streams, Gaga Lake, measuring digital caliper (Dasqua™) with 0.01 mm precision Turnasuyu Stream, Curi Stream, Elekçi Stream, Ilıca Stream as methods reported by Holčík (1989). According to morpho- and Tifi Brook (Turan et al., 2008; Darçın, 2014; Dönel and metric measurement results obtained from the study, the per- Yılmaz, 2016; Bostancı et al., 2015; 2016; Yılmaz, 2016; centages of some metric characters of fish samples were cal- Saygun et al., 2017; Turan et al. 2017). culated by proportioned of the standard length (SL%) and by In this study, it was aimed to reveal actual taxonomic status the head length (HL%) for different fish families (Holčík, of the fish species living in the Bolaman Stream. 1989; Bǎnǎrescu, 1999; Bǎnǎrescu and Bogutskaya, 2002; Bǎnǎrescu and Paepke, 2003; Miller, 2003; Verep et al., 2006; Turan et al., 2014; 2017).

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Figure 1. Fish sampling stations in the Bolaman Stream (Table 1)

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Table 1. Distribution of fish species as sampling stations in Bolaman Stream, sp: sampling points. Altitudes Species Sampling sp Coordinates (m) n Cyprinoids n Gobioids n Salmonids Date 2 A. fasciatus 40°59'15"N 17 B. tauricus 2 N. fluviatilis 1 24 - 06.07.2017 37°29'55"E 5 C. banarescui 11 P. turani 9 S. cephalus 1 A. fasciatus 11 A. derjugini 23 B. tauricus 40°56'23"N 2 N. fluviatilis 2 55 10 C. banarescui - 11.07.2017 37°29'32"E 12 P. turani 4 R. amarus 20 S. cephalus 5 V. vimba 5 C. banarescui 40°52'28"N 4 N. fluviatilis 3 163 11 R. amarus - 19.05.2018 37°26'01"E 2 P. turani 3 S. cephalus 40°51'14"N 4 753 33 C. banarescui - 5 S. coruhensis 10.11.2018 37°32'47"E 1 A. fasciatus 10 A. derjugini 40°45'21"N 4 B. tauricus 5 526 10 P. turani - 30.06.2018 37°30'38"E 2 C. banarescui 3 R. amarus 9 S. cephalus 8 A. derjugini 6 B. tauricus 40°42'01"N 6 710 2 C. banarescui 4 P. turani - 30.07.2018 37°32'58"E 5 R. amarus 2 S. cephalus 40°38'16"N 7 772 No sample 30.07.2018 37°23'10"E

Results and Discussion When looked at Figure 2, the percentages of seven cypriniform species consisted of Cyprinidae, Acheilognothidae, As a result of the study, a total of 263 specimens of 10 species and Leuciscidae were seen to be 81% (211 samples) of all were sampled in six sampling points determined on the Bo- specimens. laman Stream (Figure 2) but the seventh station because not come across to any fish species. The details of sampling sta- According to the sampling stations in the Bolaman Stream, nd tions, as well as the fish species discovered in each one of all species, except Salmo coruhensis, were found in 2 sta- them, were presented in Table 1. There were described two tion. Although all the stations of Capoeta banarescui were species from Cyprinidae, a species from Acheilognothidae, also encountered but seventh station, which allowed no fish four species Leuciscidae, two species from Gobiidae, and one species. Only two species identified in the fourth station species from Salmonidae in systematic order as follows. It which were C. banarescui and S. coruhensis (Table 1). was seen that cypriniform species were predominant as in The average percent data calculated according to some mor- other streams in the region and Ponticola turani, which is a phometric values of the fish species obtained in the Bolaman Gobioidae species, was also observed to be dense (Figure 3). Stream were represented in Tables 2, 3, and 4. In these tables,

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the values were computed in percentages proportion to dif- of unclassified samples and distribution range (m-M) for each ferent morphometric data of standard length (SL) and head sample were given in the tables. length (HL) (for all species). However, means (x̄ ) of morphometric values percentage accounted standard deviations (±)

Table 2. Mean (x̄ ) percentage values of some morphometric characteristics of Cypriniform species obtained from the Bo- laman Stream according to standard length (SL) and head length (HL). ± Standard deviation, m-M minimum-maximum values.

Barbus tauricus (n=50) Capoeta banarescui (n=57) x̄ ± m-M x̄ ± m-M Standard Length (mm) 106.50 16.31 72.61-139,62 97.70 21.02 59.39-142.62

In percent of standard length Maximum body height 20.13 1.76 17.31-24.39 20.58 1.43 16.42-22.56 Minimum body height 9.71 0.54 8.70-11.44 10.25 0.62 8.79-11.76 Caudal peduncle height 11.19 0.83 9.47-14.44 11.78 0.80 10.08-13.30 Predorsal distance 50.22 3.13 46.53-66.59 48.72 1.58 45.59-52.11 Postdorsal distance 37.46 2.86 34.04-52.73 37.19 1.73 32.86-40.17 Prepelvic distance 53.37 2.82 48.38-69.10 53.61 1.55 51.18-58.02 Preanal distance 74.20 2.23 64.74-77.86 73.94 2.28 68.90-80.10 Length of caudal peduncle 18.95 1.86 13.93-26.68 19.05 1.66 14.61-21.58 Length of dorsal fin 13.44 1.34 11.83-20.01 12.80 1.25 10.02-14.78 Dorsal fin height 19.50 1.51 16.45-25.73 20.08 1.53 17.45-24.13 Length of anal finbase 7.72 0.92 4.94-10.87 8.71 1.40 6.99-12.62 Depth of anal fin 18.09 1.32 15.51-23.23 17.71 1.40 12.46-19.54 Length of pectoral fin 18.52 1.30 15.83-23.81 18.36 1.02 15.99-19.64 Length of ventral (pelvic) fin 16.17 1.79 13.58-23.61 15.77 1.38 13.74-19.25 Distance between pectoral and pelvic fins 28.18 4.31 24.14-51.51 30.88 2.13 25.67-35.67 Distance between pelvic and anal fins 22.54 2.40 19.59-33.82 21.96 3.08 10.07-30.12 Body width 14.61 1.33 12.29-17.77 14.49 0.99 12.60-16.20 Caudal peduncle width 5.05 0.64 3.37-6.19 5.33 0.70 4.23-6.65 Head length 25.99 1.45 23.53-33.47 23.11 1.50 20.71-27.06

In percent of head length Preorbital distance (snout length) 41.25 2.13 37.33-48.13 31.95 2.98 25.36-37.95 Horizontal diameter of eye 17.68 2.31 14.39-23.54 18.05 2.50 13.18-22.96 Postorbital distance 43.67 2.48 37.09-47.57 48.09 2.62 39.69-53.62 Head depth (at nape) 58.13 3.36 50.98-66.98 65.23 6.13 59.19-94.45 Head depth (at center of eye) 44.39 3.61 39.02-53.04 48.37 2.73 42.56-55.51 Head width 51.96 4.37 43.10-63.47 55.64 5.49 38.87-68.00 Interorbital distance 30.18 2.20 25.07-34.84 36.18 3.37 23.50-42.75 Distance between nostrils 17.42 1.85 13.69-24.23 22.76 2.99 16.66-28-94 Length of anterior barbel 18.59 1.99 12.72-22.45 16.21 3.26 10.66-24.46 Length of posterior barbel 22.70 2.29 17.60-27.23 20.16 3.56 13.10-27.96

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continuation of Table 2 Rhodeus amarus (n=23) x̄ ± m-M Standard Length (mm) 106.50 16.31 72.61-139.62

In percent of standard length Maximum body height 21.73 1.21 19.04-23.69 Minimum body height 10.82 0.63 9.68-12.09 Caudal peduncle height 12.51 0.82 10.85-13.96 Predorsal distance 52.01 1.82 49.77-56.35 Postdorsal distance 36.77 2.07 31.50-39.74 Prepelvic distance 49.08 0.96 47.64-50.97 Preanal distance 70.64 4.40 67.08-87.50 Length of caudal peduncle 21.20 1.51 18.51-23.51 Length of dorsal fin 10.90 1.08 9.34-13.58 Dorsal fin height 18.30 1.46 15.74-20.98 Length of anal finbase 10.43 0.72 9.06-11.56 Depth of anal fin 15.90 0.85 13.80-17.11 Length of pectoral fin 17.04 1.16 14.38-19.18 Length of ventral (pelvic) fin 13.75 0.76 12.69-15.74 Distance between pectoral and pelvic fins 25.46 1.60 22.56-28.70 Distance between pelvic and anal fins 20.80 0.79 19.54-22.23 Body width 13.87 1.34 11.09-15.88 Caudal peduncle width 5.31 0.83 3.66-6.66 Head length 24.32 0.93 22.78-26.42

In percent of head length Preorbital distance (snout length) 27.87 2.63 23.60-32.68 Horizontal diameter of eye 21.26 1.87 17.85-25.38 Postorbital distance 52.71 3.11 47.32-61.55 Head depth (at nape) 66.29 4.18 54.33-72.77 Head depth (at center of eye) 48.77 2.61 42.98-54.57 Head width 55.14 4.83 45.17-64.33 Interorbital distance 36.93 3.22 31.57-42.90 Distance between nostrils 21.45 2.56 16.24-27.68

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continuation of Table 2

Alburnus derjugini (n=29) Squalius cephalus (n=43) x̄ ± m-M x̄ ± m-M Standard Length (mm) 102.79 15.84 62.24-133.19 97.49 25.98 57.74-150.22

In percent of standard length Maximum body height 19.98 0.95 17.43-21.77 26.61 1.12 25.88-28.83 Minimum body height 8.08 0.42 7.30-8.97 9.70 0.08 9.59-9.80 Caudal peduncle height 10.37 0.75 9.24-12.63 11.52 0.72 10.51-12.40 Predorsal distance 52.63 6.73 20.40-56.88 51.74 0.53 50.84-52.45 Postdorsal distance 35.34 1.75 32.86-40.30 38.70 1.66 35.80-40.18 Prepelvic distance 46.12 1.31 43.09-48.43 48.22 1.31 46.14-49.71 Preanal distance 64.82 2.01 60.86-70.23 66.89 1.91 64.57-70.16 Length of caudal peduncle 21.21 1.47 18.06-23.72 18.20 1.66 16.03-20.49 Length of dorsal fin 11.05 1.06 9.16-12.97 12.22 0.53 11.36-12.91 Dorsal fin height 16.52 1.54 13.73-19.99 21.34 2.32 18.08-24.16 Length of anal finbase 15.69 1.17 13.44-17.64 18.44 0.99 16.53-19.18 Depth of anal fin 12.36 1.32 10.13-15.24 13.46 1.05 12.04-14.77 Length of pectoral fin 18.02 1.40 15.21-20.44 18.07 0.98 16.80-19.36 Length of ventral (pelvic) fin 13.57 1.53 11.11-19.49 16.24 0.66 15.10-16.85 Distance between pectoral and pelvic fins 24.77 1.33 21.69-27.43 21.52 0.91 19.77-22.42 Distance between pelvic and anal fins 18.94 1.13 16.79-21.67 21.11 0.91 19.55-22.07 Body width 12.21 1.46 10.00-16.05 12.86 0.88 11.56-13.86 Caudal peduncle width 5.06 0.54 4.08-6.13 4.36 0.21 4.13-4.61 Head length 23.13 1.98 20.91-31.97 24.94 0.61 24.07-25.74

In percent of head length Preorbital distance (snout length) 29.78 3.13 20.32-34.63 31.47 2.75 28.79-35.39 Horizontal diameter of eye 25.55 3.35 18.43-31.75 21.98 1.11 20.16-23.55 Postorbital distance 43.65 4.44 30.11-49.70 46.43 2.42 42.85-49.61 Head depth (at nape) 63.73 5.24 44.66-73.64 71.46 3.69 67.69-78.12 Head depth (at center of eye) 47.65 4.08 35.50-54.81 53.06 2.65 50.58-56.89 Head width 45.61 3.56 31.75-49.05 48.34 1.08 46.49-49.39 Interorbital distance 28.78 3.59 20.94-40.58 31.86 2.33 29.46-35.77 Distance between nostrils 14.48 2.51 8.69-19.94 17.25 1.09 15.72-18.25

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continuation of Table 2

Vimba vimba (n=5) Alburnoides fasciatus (n=4) x̄ ± m-M x̄ ± m-M Standard Length (mm) 115.86 5.26 105.75-120.23 67.39 1.77 64.41-69.06

In percent of standard length Maximum body height 26.61 1.12 19.04-23.69 20.47 0.88 19.15-21.47 Minimum body height 9.70 0.08 9.68-12.09 8.25 0.26 7.90-8.57 Caudal peduncle height 11.52 0.72 10.85-13.96 9.77 0.37 9.18-10.11 Predorsal distance 51.74 0.53 49.77-56.35 42.67 2.07 41.28-46.24 Postdorsal distance 38.70 1.66 31.50-39.74 29.88 1.29 28.19-31.73 Prepelvic distance 48.22 1.31 47.64-50.97 39.20 2.03 36.80-42.41 Preanal distance 66.89 1.91 67.08-87.50 17.43 0.76 16.17-18.10 Length of caudal peduncle 18.20 1.66 18.51-23.51 16.05 0.49 15.65-16.89 Length of dorsal fin 12.22 0.53 9.34-13.58 11.93 1.17 10.53-13.76 Dorsal fin height 21.34 2.32 15.74-20.98 17.11 3.28 11.96-21.04 Length of anal finbase 18.44 0.99 9.06-11.56 14.98 2.08 11.78-17.13 Depth of anal fin 13.46 1.05 13.80-17.11 14.38 1.41 12.45-16.08 Length of pectoral fin 18.07 0.98 14.38-19.18 17.43 0.76 16.17-18.10 Length of ventral (pelvic) fin 16.24 0.66 12.69-15.74 14.63 0.59 13.65-15.21 Distance between pectoral and pelvic fins 21.52 0.91 22.56-28.70 20.11 0.84 18.79-21.07 Distance between pelvic and anal fins 21.11 0.91 19.54-22.23 16.99 2.26 14.39-20.58 Body width 12.86 0.88 11.09-15.88 10.31 0.37 9.90-10.86 Caudal peduncle width 4.36 0.21 3.66-6.66 4.59 0.37 4.08-5.11 Head length 24.94 0.61 22.78-26.42 20.06 0.17 19.89-20.34

In percent of head length Preorbital distance (snout length) 31.47 2.75 23.60-32.68 26.95 2.66 23.13-29.56 Horizontal diameter of eye 21.98 1.11 17.85-25.38 27.49 3.05 22.35-30.04 Postorbital distance 46.43 2.42 47.32-61.55 46.32 2.16 42.63-48.12 Head depth (at nape) 71.46 3.69 54.33-72.77 73.54 1.72 71.88-76.38 Head depth (at center of eye) 53.06 2.65 42.98-54.57 55.40 3.80 51.39-61.54 Head width 48.34 1.08 45.17-64.33 47.35 3.28 44.98-52.94 Interorbital distance 31.86 2.33 31.57-42.90 34.03 3.46 31.14-39.93 Distance between nostrils 17.25 1.09 16.24-27.68 15.92 2.42 13.09-19.78

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0 20 40 60 80 100 120

Cyprinidae

Acheilognathidae

Leuciscidae

Gobiidae

Salmonidae

Salmonidae Gobiidae Leuciscidae Acheilognathidae Cyprinidae Species Quantity 1 2 4 1 2 n (Sample) 5 47 81 23 107 n % 1,90 17,87 30,80 8,75 40,68

Figure 2. Families’ distribution of Bolaman Stream according to specimen quantity

57 Capoeta banarescui 22 50 Barbus tauricus 19 23 Rhodeus amarus 9 4 Alburnoides fasciatus 2 29 Alburnus derjugini 11 43 Squalius cephalus 16 5 Vimba vimba 2 8 Neogobius fluviatilis 3 39 Ponticola turani 15 5 Salmo coruhensis 2 0 10 20 30 40 50 60

n n %

Figure 3. Number of samples (n) and percentage ratios (n %) of fish species obtained from Bolaman Stream

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Family: Cyprinidae Barbus tauricus is a barbel fish and the second most common species of cyprinoids in the Bolaman Stream. Results of mor- Capoeta banarescui Turan, Kottelat, Ekmekçi & Imamo- phometric measurement ratios percent procured from forty ğlu, 2006 (Figure 4) specimens of Crimean barbell were presented in Table 2. As Examined Material. ODUFFMS 52410-06040, 5, 59.39- the numerical counts of meristic characters were fixed to be 142.62 mm SL; Turkey: Karataş, Fatsa/Ordu: Bolaman D I/9, P I/8-9, V I/7-8, A I/5 and LL 50-58. Stream; S. Saygun, 06 Jul 2017. – ODUFFMS 52410-06041, 10, 83.52-123.74 mm SL; Örencik, Fatsa/Ordu: Bolaman Stream; S. Saygun, 11 Jul 2017. – ODUFFMS 52420-06042, 5, 98.09-122.40 mm SL; Dere, Çatalpınar/Ordu: Karakoyun Stream; S. Saygun, 19 May 2018. – ODUFFMS 52430- 06043, 33, 70.82-100.98 mm SL; Kestaneyokuşu, Çamaş/Ordu: Bolaman Stream; S. Saygun, 10 Nov 2018. – ODUFFMS 52600-06044, 2, 115.65-116.52 mm SL; Direkli, Gölköy/Ordu: Bolaman Stream; S. Saygun, 30 Jun 2018. – ODUFFMS 52600-06045, 2, 81.37-122.43 mm SL; Çetilli, Figure 5. Barbus tauricus, ODUFFMS 52410-06030, 95.67 Gölköy/Ordu: Bolaman Stream; S. Saygun, 30 Jul 2018. mm SL; Turkey: Bolaman Stream Family: Acheilognothidae Rhodeus amarus (Bloch, 1872) (Figure 6) Examined Material. ODUFFMS 52410-06070, 4, 47.30- 57.06 mm SL; Örencik, Fatsa/Ordu: Bolaman Stream; S. Saygun, 11 Jul 2017. – ODUFFMS 52430-06071, 11, 40.39- 61.28 mm SL; Dere, Çatalpınar/Ordu: Karakoyun Stream; S. Saygun, 19 May 2018. – ODUFFMS 52600-06072, 3, 42.48- Figure 4. Capoeta banarescui, ODUFFMS 52410-06040, 46.05 SL; Direkli, Gölköy/Ordu: Bolaman Stream; S. 142.62 mm SL; Turkey: Bolaman Stream Saygun, 30 Jun 2018. – ODUFFMS 52600-06073, 1, 36.22- Capoeta banarescui including in Cyprinidae is known as one 60.16 mm SL; Çetilli, Gölköy/Ordu: Bolaman Stream; S. of the widely resident species in Turkish freshwaters through Saygun, 30 Jul 2018. The Middle and East Blacksea Regions. Their distributions are only accepted from northeast Turkey from the Çoruh River system, which drains through Georgia and the Black Sea. Turan et al. (2006) reported that it was a different species from Capoeta tinca. In the study, C. banarescui was obtained at every stations except two sampling points as the second most common Cyprinoid species in the Bolaman Stream. The meristic characters of this barbel fish were designated as D I/7-8, A I/12-14, P I/14-15, V I/8 and LL 65-69. Morphomet- ric ratios percent were shown in Table 2. Figure 6. Rhodeus amarus, ODUFFMS 52410-06070, Barbus tauricus Kessler, 1877 (Figure 5) 55.28 mm SL; Turkey: Bolaman Stream Examined Material. ODUFFMS 52410-06030, 17, 72.61- The European bitterling (Rhodeus amarus) originates in Eu- 139.62 mm SL; Turkey: Karataş, Fatsa/Ordu: Bolaman rope, ranging from the Rhone River basin in France to the Stream; S. Saygun, 06 Jul 2017. – ODUFFMS 52410-06031, Neva River in Russia. It was originally described as Cyprinus 23, 83.85-129.15 mm SL; Örencik, Fatsa/Ordu: Bolaman amarus by Marcus Elieser Bloch in 1782 and has been re- Stream; S. Saygun, 11 Jul 2017. – ODUFFMS 52600-06032, ferred to in scientific literature as Rhodeus sericeus amarus 4, 76.92-127.27 mm SL; Direkli, Gölköy/Ordu: Bolaman (Kottelat & Freyhof, 2007). However, while it was previously Stream; S. Saygun, 10 Nov 2018. – ODUFFMS 52600- estimated to found a subspecies of Rhodeus sericeus in Tur- 06033, 6, 88.39-125.70 mm SL; Çetilli, Gölköy/Ordu: Bo- key's freshwaters, R. amarus was determined to be only one laman Stream; S. Saygun, 30 Jun 2018.

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species belonging to Acheilognothidae (Tan and Armbruster, 2018) family in Turkey (Bektaş et al., 2013). In this study, 23 European Bitterling specimens were caught at four stations (2nd, 3rd, 5th, and 6th stations) at the Bolaman Stream (Table 1). Results of the morphometric percent ratios of these specimens were represented in Table 2. Looking at meristic specialties being the other characters of bitterling, were counted that D I/8-9, A I/8-9, P I/6-8, V I/6 and LL 35- 38 in the research. Figure 8. Alburnus derjugini, ODUFFMS 52410-06020, 98.05 mm SL; Turkey: Bolaman Stream Family: Leuciscidae The Georgian shemaya (Alburnus derjugini), a species of Cy- Alburnoides fasciatus (Nordmann, 1840) (Figure 7) prinoid fish in the genus Alburnus and collected also in the Examined Material. ODUFFMS 52410-06010, 2, 52.48- Bolaman Stream, distributed in eastern Black Sea tributaries, 56.11 mm SL, Turkey: Karataş, Fatsa/Ordu: Bolaman from south of the Caucasus in Russia and Georgia, to the Stream; S. Saygun, 06 Jul 2017. – ODUFFMS 52420-06011, south the Çoruh River in eastern Anatolia and to the west the 1, 57.66 mm SL; Örencik, Fatsa/Ordu: Bolaman Stream; S. Sakarya River (Freyhof, 2014). According to the latest pub- Saygun, 11 Jul 2017. – ODUFFMS 52600-06012, 1, 56.07 lished molecular phylogenetic study (Bektaş et al., 2020), A. mm SL; Direkli, Gölköy/Ordu: Bolaman Stream; S. Saygun, derjugini was determined that synonymized species of A. is- 30 Jun 2018. tanbulensis, A. carinatus and A. schischkovi. A. derjugini was one of the common cyprinoid species in the Bolaman Stream and had an 11% ratio into total fish samples in a rank of fourth (Figure 3). The countable characters of Georgian Shemaya were defined being D I/8, A I/13-14, P I/12-13, V I/8 and LL 57-60. Percent ratios as to metric measurements of 27 samples from the Bolaman Stream were represented in Table 2.

Squalius cephalus (Figure 9) Figure 7. Alburnoides fasciatus, ODUFFMS 52410- (Linneaus, 1758) 06010, 56.11 mm SL; Turkey: Bolaman Stream Examined Material. ODUFFMS 52410-06090, 9, 57.74- In the study, the Transcaucasian Sprilin, Alburnoides fascia- 150.22 mm SL; Turkey: Karataş, Fatsa/Ordu: Bolaman tus was obtained the least number of the sample with four Stream; S. Saygun, 06 Jul 2017. – ODUFFMS 52410-06091, specimens from the Bolaman Stream. Morphometric percent 20, 65.65-138.14 mm SL; Örencik, Fatsa/Ordu: Bolaman ratios of A. fasciatus samples was shown in Table 2. The me- Stream; S. Saygun, 11 Jul 2017. – ODUFFMS 52420-06092, ristic characters of this species were determined D I/8-9, A 3, 113.97-121.49 mm SL; Dere, Çatalpınar/Ordu: Karakoyun Stream; S. Saygun, 19 May 2018. – ODUFFMS 52600- I/12-14, P I/11-12, V I/7 and LL 42-45. 06093, 9, 74.02-118.80 mm SL; Direkli, Gölköy/Ordu: Bo- Alburnus derjugini Berg, 1923 (Figure 8) laman Stream; S. Saygun, 30 Jun 2018. – ODUFFMS 52600- 06094, 2, 79.02-118.65 mm SL; Çetilli, Gölköy/Ordu: Bo- ODUFFMS 52410-06020, 11, 91.12- Examined Material. laman Stream; S. Saygun, 30 Jul 2018. 101.54 mm SL; Örencik, Fatsa/Ordu: Bolaman Stream; S. Saygun, 11 Jul 2017. – ODUFFMS 52420-06021, 8, 95.85- 128.94 mm SL; Dere, Çatalpınar/Ordu: Karakoyun Stream; S. Saygun, 19 May 2018. – ODUFFMS 52600-06022, 10, 62.24-133.19 mm SL; Direkli, Gölköy/Ordu: Bolaman Stream; S. Saygun, 30 Jun 2018.

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Stream; S. Saygun, 06 Jul 2017. – ODUFFMS 52410-06051, 2, 88.96-106.72 mm SL; Örencik, Fatsa/Ordu: Bolaman Stream; S. Saygun, 11 Jul 2017. – ODUFFMS 52420-06052, 4, 59.56-105.93 mm SL; Dere, Çatalpınar/Ordu: Karakoyun Stream; S. Saygun, 19 May 2018.

Figure 9. Squalius cephalus, ODUFFMS 52410-06090, 150.22 mm SL; Turkey: Bolaman Stream The Squalius living from the rivers of the European and eastern Black Sea are usually identified as S. cephalus (Kottelat and Freyhof, 2007). S. orientalis is available for the ‘Eastern’ lineage while they temporarily use S. cephalus for the ‘West- ern’ lineage (Özuluğ and Freyhof, 2011). Squalius sampled Figure 11. Neogobius fluviatilis, ODUFFMS 52410-06050, in our study indicated that it belongs to the Western lineages. 94.24 mm SL; Turkey: Bolaman Stream Squalius cephalus (Chub) sample shown in Figure 9 was one of the 43 samples procured from the Bolaman Stream. In the Neogobius fluviatilis shown a specimen in Figure 11 were Table 2, morphometric ratios percent of this species were sampled eight specimens in the Bolaman Stream in this study. shown. The meristic results were detected D I/8, A I/8, P I/12- It was counted and measured their meristic and metric char- 13, V I/7-8 and LL 42-44. acters of Monkey goby specimens. The meristic characters were indicated to be D1 V, D2 14-18, A I/13-14, LL 66-69. Vimba vimba (Linnaeus, 1758) (Figure 10) In the Table 3, morphometric percent ratios of this species Examined Material. ODUFFMS 52410-06100, 5, 105.75- were shown. 120.23 mm SL; Örencik, Fatsa/Ordu: Bolaman Stream; S. Ponticola turani (Kovačić & Engin, 2008) (Figure 12) Saygun, 11 Jul 2017. Examined Material. ODUFFMS 52410-06060, 11, 79.32- 111.09 mm SL; Turkey: Karataş, Fatsa/Ordu: Bolaman Stream; S. Saygun, 06 Jul 2017. – ODUFFMS 52410-06061, 12, 84.35-108.18 mm SL; Örencik, Fatsa/Ordu: Bolaman Stream; S. Saygun, 11 Jul 2017. – ODUFFMS 52420-06062, 2, 67.67-91.32 mm SL; Dere, Çatalpınar/Ordu: Karakoyun Stream; S. Saygun, 19 May 2018. – ODUFFMS 52600- 06063, 10, 77.00-110.98 mm SL; Direkli, Gölköy/Ordu: Bo- laman Stream; S. Saygun, 30 Jun 2018. – ODUFFMS 52600- 06064, 4, 67.94-91.89 mm SL; Çetilli, Gölköy/Ordu: Bo-

laman Stream; S. Saygun, 30 Jul 2018. Figure 10. Vimba vimba, ODUFFMS 52410-06100, 120.13 mm SL; Turkey: Bolaman Stream Vimba vimba species was one of the two species that collected the minimum number in the Bolaman Stream. Five specimens captured from the only the second station was measured and counted some metric characters. The counting characters were found D I/8, A I/13-14, P I/13-14, V I/8 and LL 50-54. Looking at the Table 2, the percentages of morphometric measurements ratios were given in this species.

Family: Gobiidae Figure 12. Ponticola turani, ODUFFMS 52410-06060, Neogobius fluviatilis (Pallas, 1814) (Figure 11) 111.09 mm SL; Turkey: Bolaman Stream Examined Material. ODUFFMS 52450-06040, 2, 82.55- 94.24 mm SL; Turkey: Karataş, Fatsa/Ordu: Bolaman

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Aksu goby, one of the endemic species of Turkey, was the to the distribution of fish species in the stream, the least in- fourth most caught species in the Bolaman Stream (Figure 3). tense sampled species were about 2% of Alburnoides fascia- Percent ratios as to metric measurements of specimens from tus, Salmo coruhensis and Vimba vimba. The Ponticola tu- the Bolaman Stream were represented in Table 3. Countable rani (approx. 15%) was the most common forth species after characters were found to be D1 VI, D2 15-16, A I/11-14, LL C. banarecui, B. tauricus and S. cephalus. As a single species, 60-65. Salmo coruhensis from Salmonidae family and Rhodeus amarus species from Acheilognothidae family were obtained. Family: Salmonidae However, when the distribution in stations of the samples ob- Salmo coruhensis Turan, Kottelat & Engin, 2010 (Figure tained in the study was examined, the second station (nine 13) species) has the highest number of species compared to other sampling points. Examined Material. ODUFFMS 52430-06080, 5, 116.94- 230.50 mm SL; Kestaneyokuşu, Çamaş/Ordu: Bolaman Squalius cephalus and S. orientalis are two species that are Stream; S. Saygun, 10 Nov 2018. similar to each other and have been difficulty distinguished. Berg (1949) had identified S. cephalus from S. orientalis (as The Çoruh trout, one of the endemic species in North inland subspecies of S. cephalus) by the number of branched anal- waters of Turkey, was observed in this study, too. Salmo fin rays (usually 81/2 in S. cephalus vs. usually 91/2 in S. ori- coruhensis, which is living commonly in cold streams of entalis) and body shape (body more elongate in S. orientalis) Eastern Black Sea in Turkey and which is described as a new (Özuluğ and Freyhof, 2011). 95% of the 43 samples endemic species by Turan et al. (2009), is still accepted as a (ODUFFMS 52410-06090) obtained in this study had the valid species in taxonomic literature but, in a molecular study specified feature which are quite elongate and have all 81/2 performed by Kalaycı et al. (2018) it was reported that this branched anal-fin rays. species and similar salmonid species are from the Danube lineage of brown trout (Salmo trutta). S. coruhensis, which nat- As the conclusion of this study, for the first time, it was iden- urally lives in higher places compared to other species, has tified ten species in five different genera belonging to five also been found at approx. 753m altitude (Table 1) of the families (Acheilognothidae, Cyprinidae, Gobiidae, Leucis- stream in this study. In the seventh station, the highest sam- cidae, and Salmonidae) in the Bolaman Stream. During the pling point, it was unbelievable not to come across neither sampling performed, it was seen that there is pollution in sec- salmonids nor any fish species. The meristic data were tions, which also is less the water than the main riverbed and counted D I/10-12, A I/9-10, P I/12, V I/8-9 and LL 87-90. even in the high parts of the stream. Moreover, it was determined that there are few or no species at some stations, where environmental conditions threaten the habitats of the fish in the research. According to data obtained from samplings conducted in the study during the summer months, the Hydroe- lectric Power Plants founded on the Bolaman Stream have been observed that been threaten enough water regime for the survival of fish. Contrary to what I expect in this study, it is possible to say that environmental conditions threaten the Figure 13. Salmo coruhensis, ODUFFMS 52430-06080, habitat of fishes along the stream as a result of taking more 230.50 mm SL; Turkey: Bolaman Stream fish samples of different species from small streams that flow Some morphometric characters of S. coruhensis specimens into the Bolaman Stream and are relatively cleaner than the were accounted for as a percentage ratio according to stand- stream. The fact that no samples of any species were not ob- th ard length (SL) and head length (HL). Morphometric percent- tained from a station (7 st) on one of the highest elevations age ratios of this species were shown in Table 4. can be also an indication of this. Monitoring of changes threatening the future of fauna and flora in the stream and Conclusion more detailed physicochemical and taxonomic studies are needed within or after a decade. In this study, the number of species in the Bolaman Stream was also the highest in the Cyprinoid species with about 80% (211 samples), but the Barbus and Capoeta species were approx. 41% of the total sample number (Figure 2). According

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Table 3. Mean (x̄ ) percentage ratios of some morphometric characters of Gobioid species obtained from the Bolaman Stream according to standard length and head length. ± Standard deviation, m-M minimum-maximum values

Neogobius fluviatilis (n=8) Ponticola turani (n=39) x̄ ± m-M x̄ ± m-M Standard Length (mm) 83.46 17.68 59.56-106.72 93.35 11.33 67.67-111.09

In percent of standard length Length of head 26.84 0.82 25.78-28.39 27.50 1.66 22.01-30.14 Head depth (at nape) 15.27 1.36 13.48-17.13 18.16 2.13 13.61-24.59 Predorsal distance 1 31.84 1.46 29.67-34.13 32.71 3.09 27.53-48.80 Predorsal distance 2 46.34 2.83 39.83-49.50 47.37 1.68 43.88-50.93 Pength of dorsal fin 2 40.30 1.10 37.73-41.73 46.25 2.50 38.36-51.72 Dorsal fin heigth2 13.76 1.57 11.48-17.06 29.40 3.60 22.50-41.84 Length of pectoral fin 23.14 2.39 19.17-27.37 21.82 2.87 11.55-29.16 Length of pelvic fin 19.20 1.82 16.19-21.90 16.45 1.18 14.17-18.79 Length of anal finbase 30.95 2.45 26.82-35.63 27.42 1.76 23.04-31.03 Length of caudal peduncle 18.23 1.62 15.81-20.69 17.78 2.33 12.90-22.74 Minimum body height 7.02 0.26 6.53-7.37 9.56 0.56 8.40-10.60 Maximum body height 17.06 1.40 14.52-19.11 19.98 1.33 16.19-22.52 Head width 17.19 2.08 15.21-22.07 21.58 1.73 18.24-25.44

In percent of head length Preorbital distance 35.21 1.56 33.90-39.13 32.05 5.03 22.88-48.68 Horizontal diameter of eye 17.74 1.75 14.84-21.32 19.31 2.15 15.23-24.01 Postorbital distance 50.18 2.82 46.17-54.67 52.18 6.16 41.65-74.13 Head depth (at nape) 56.98 5.88 48.30-65.35 66.19 8.08 53.04-89.67 Head width 64.08 7.78 55.04-81.01 78.74 7.74 64.01-98.03 Interorbital distance 15.99 3.43 9.84-21.77 13.44 2.56 8.64-21.18

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Table 4. Mean (x̄ ) percentage ratios of some morphometric characters of Salmo coruhensis from the Bolaman Stream to standard length and head length, ± Standard deviation, m-M minimum-maximum values Salmo coruhensis (n=5) x̄ ± m-M Standard Length (mm) 163.49 50.69 116.94-230.50

In percent of standard length head length 25.98 2.01 24.11-29.88 Maximum body height 21.96 1.20 20.59-23.90 Minimum body height 9.28 0.73 8.24-10.28 Predorsal distance 45.06 1.26 43.64-46.76 Postdorsal distance 41.73 2.08 39.63-45.55 Length of adipose finbase 4.00 0.49 3.20-4.58 Distance between adipose and caudal finbases 16.94 1.07 15.35-18.56 Prepelvic distance 54.19 1.84 51.97-56.82 Preanal distance 70.91 1.01 69.55-72.21 Distance between pectoral and pelvic fins 30.00 0.86 29.05-31.32 Dist. between pelvic and anal fins 19.62 0.61 18.91-20.34 Length of caudal peduncle 19.09 1.54 16.79-21.15 Length of dorsal fin 13.89 0.89 12.77-15.07 Dorsal fin heigth 18.47 1.62 15.86-20.16 Length of anal finbase 10.84 1.14 9.76-12.81 Depth of anal fin 15.44 1.41 13.21-16.73 Length of pectoral fin 18.13 1.07 17.28-20.23 Length of pelvic fin 14.22 0.69 13.11-15.16

In percent of head length Head depth (at nape) 61.82 5.17 54.11-69.50 Head depth (at center of eye) 47.87 3.53 42.68-52.10 Preorbital distance 27.65 1.17 25.97-29.02 Horizontal diameter of eye 20.41 1.25 18.97-22.70 Interorbital distance 29.24 1.46 27.52-31.43 Postorbital distance 50.57 2.85 47.34-54.91 Depth of upper jaw 12.39 0.71 11.11-13.27 Upper jaw length 48.63 2.14 46.07-51.13 Lower jaw length 68.38 10.00 59.09-83.96

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Compliance with Ethical Standard Bitterling, Rhodeus amarus (Osteichthyes: Cyprinoidae). Zo- Conflict of interests: The authors declare that for this article they ology in the Middle East, 59(1), 39-50. have no actual, potential or perceived conflict of interests. https://doi.org/10.1080/09397140.2013.795063

Ethics committee approval: This study was approved with Docu- Bektas, Y., Aksu, I., Kaya, C., Bayçelebi, E., Küçük, F., ment Number and Date of 82678388 / 27.01.2016 given by Ordu University Animal Experiments Local Ethics Committee Approval Turan, D. (2020). Molecular systematics and phylogeogra- Document. phy of the genus Alburnus Rafinesque, 1820 (Teleostei, Leu- ciscidae) in Turkey. Mitochondrial DNA Part A, 31(7), 273- Funding disclosure: This study was supported by Research Project 284. AR-1697 by Ordu University Scientific Projects Support Coordina- https://doi.org/10.1080/24701394.2020.1791840 tion Department.

Acknowledgments: I would like to thanks a lot our staff Halil Bostancı, D., İskender, R., Helli, S., Polat, P. (2015). SULUK and Abdülkerim GÖNEZ for their valuable time and ef- Turnasuyu Deresi (Ordu) balık faunasının belirlenmesi. Ordu forts in field surveys. I would also like to thank Enes Fatih PEH- Üniversitesi Bilim ve Teknoloji Dergisi, 5(2), 1-9. LİVAN and Filiz SAYGUN for their contributions in the laboratory studies. Bostancı, D., İskender, R., Helli, S., Polat, N. (2016). The Disclosure: Some information’s in this article were presented fish of the Curi stream (Ordu) and invasive fish species orally at an international symposium and is included in the abstract Carassius gibelio (Bloch, 1782). Journal of Aquaculture En- booklet in International Marine & Freshwater Sciences Sympo- gineering and Fisheries Research, 2(1), 11-19. sium, 18-21 October 2018, Kemer-Antalya / Turkey. https://doi.org/10.3153/JAEFR16002

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54 AQUATIC RESEARCH

E-ISSN 2618-6365

Aquat Res 4(1), 55-64 (2021) • https://doi.org/10.3153/AR21005 Short Communication

A review on maximum length of the greater weever Trachinus draco Linnaeus 1758 (Perciformes: Trachinidae) with a new maximum length from Oran Bay (Western Algeria)

Lotfi BENSAHLA-TALET1,2 , Hichem ADDA NEGGAZ2

Cite this article as: Bensahla-Talet, L., Adda Neggaz, H. (2021). A review on maximum length of the greater weever Trachinus draco Linnaeus 1758 (Perciformes: Tachi- nidae) with a new maximum length from Oran Bay (Western Algeria). Aquatic Research, 4(1), 55-64. https://doi.org/10.3153/AR21005

1 University Oran1 Ahmed Benbella, ABSTRACT Faculty of Natural Science and Life, Department of Biology, Laboratory of On the 15th April 2017, one female specimen of the greater weever, Trachinus draco measuring Aquaculture and Bioremediation 44.69 cm in total length and weighting 885 g was captured by trammel net in Oran Bay (Cape (AQUABIOR), 31000, Oran Algeria. Rousseau) at 120 m depth. Up to date, this length is a new record of maximum length reached for 2 University Oran1 Ahmed Benbella, this trachinidae for Algerian waters and the second maximum length recorded in Mediterranean Faculty of Natural Science and Life, basin according to Fischer et al., 1987 observation noted at 45 cm. Department of Biology, Laboratory Environmental Monitoring Network Keywords: The greater weever, Trachinus draco, Maximum size, Oran Bay, Mediterranean Sea (LRSE), 31000, Oran Algeria.

ORCID IDs of the author(s): L.B.T. 0000-0002-8360-2079 H.A.N. 0000-0002-5672-5129

Submitted: 28.05.2020 Revision requested: 07.07.2020 Last revision received: 13.07.2020 Accepted: 13.07.2020 Published online: 23.11.2020

Correspondence: Lotfi BENSAHLA-TALET E-mail: [email protected]

Available online at http://aquatres.scientificwebjournals.com

Aquat Res 4(1), 55-64 (2021) • https://doi.org/10.3153/AR21005 Short Communication

Introduction The greater weever is a trachinidae found in Eastern Atlantic; In this context, updating the maximum size of a species har- Norway to Morocco, Madeira and Canary Islands, including vested for commercial or recreational purposes is gaining the Mediterranean and the Black Sea (Fischer et al., 1987; more importance (Borges, 2001; Dulčić and Soldo, 2005; FishBase: Froese and Pauly, 2020). Trachinus draco Lin- Akyol and Şen, 2008). The maximum observed length is a naeus 1758 inhabits sandy, muddy or gravelly bottoms, from useful tool for a rapid evaluation of growth rates in the ab- a few meters to about 150 m. Rest on the bottom, often buried sence of basic data (Legendre and Albaret, 1991, Froese and with eyes and tip of first dorsal fin exposed (Frimodt, 1995). Binohlan, 2000). To date, for Algerian waters no such studies The first dorsal fin rays, as well as the spine on the pre-oper- were leaded on this trachinidae. culum contains venomous spines protecting the species from Material and Methods predators. During night, the greater weever leaves the burrow th to feed on small invertebrates and fishes (Carpenter et al., On the 15 April 2017, one female specimen of the greater 2015). At night, it also swims around freely, even pelagically weever, Trachinus draco measuring 44.69 cm in total length (Muus and Nielsen 1999). T. draco is oviparous, eggs and and weighting 885 g was captured by captured by trammel larval stages are pelagic (Tortonese, 1986). There are dark net operating in Oran Bay (Cape Rousseau: 35°48'45.0"N markings along the scales; the anterior dorsal fin is black and 0°36'46.8"W) on sandy/rocky bottom at 120 m depth (Fig. contains venomous spines. Its length is very common be- 1). tween 10 and 30 cm with a maximum of 45 cm in the Medi- terranean and common between 15 to 20 cm with a maximum of 36 cm in the Black Sea (Fischer et al., 1987). Available bibliography for T. draco is diversified dealing with reproduction (Bagge, 2004; Ak and Genç, 2013), Para- sites (Azizi et al., 2016; Kayiş and Er, 2016), lipid content (Loukas et al., 2010), feeding habits (Santic et al., 2016), population structure and dynamics (Quigley, 1994; Portillo Strempel et al., 2008; Buz and Basusta, 2015; Carpenter et al., 2015; Custovic et al., 2014) but most of them focused on envenomation and toxin properties (Muir evans 1907; Skeie, 1962; Chahl and Kirk, 1975; Perriere and Michel, 1986; Halstead and Vinci, 1987; Chhatwal and Dreyer, 1992; Figure 1. Sampling location of greater weever (Trachinus Bouree and Lançon, 2002; Church and Hodgson, 2002; Ac- draco) specimen. ciaro et al., 2003; Verdiglione et al., 2003; Berger and The specimen was measured with an electronic caliper to 0.1 Caumes, 2004; Russell and Emery, 2006; Lopacinski et al., mm precision and weighted to the nearest 0.1 g then photo- 2009; Benlier et al., 2010; Portillo Strempel and Ceballos, graphed. Eighteen morphometric characteristics were meas- 2012) and mainly on weight length relationship (Dorel 1986; ured (Figure 2): Total length (TL), Fork length (FL), Standard Coull et al., 1989; Gonçalves et al., 1997; Merella et al., length (SL), Pectoral fin length (LP), Ventral fin length (LV), 1st 1997; Moutopoulos and Stergiou, 2002; Mendes et al., 2004; dorsal fin length (LD1), 2nd dorsal fin length (LD2), Cephalic Mendes et al., 2006; Ozaydin et al., 2007; Karakulak et al., length (LC), Maxillary length (LM), Post-orbital distance (POD1), 2006; lkyaz et al., 2008; Mata et al., 2008; Ak et al., 2009; Eye diameter (O), Post-orbital distance (POD2), Pre-ventral fin Giacalone et al., 2010; Benmessaoud et al., 2015; Öztekin et distance (PVD1), Post-ventral fin distance (PVD2), Anal fin al., 2016; Özdemir et al., 2017; Hamed et al., 2016). length (LA), Post-anal fin distance (PAD), Caudal peduncle mini- In fisheries science maximum length and maximum age are mal depth (T), Maximum body height (TPC), Total weight (TW). important theoretical parameters found as entry data in ma- Description, measurements and percentage of each body part are jority of the models used in stock assessments (Allen, 1971; reported to total length are given in (Table 1). Pauly, 1980; Welcomme, 1999; Froese and Binohlan, 2000).

Aquat Res 4(1), 55-64 (2021) • https://doi.org/10.3153/AR21005 Short Communication

Total length (TL), Fork length (FL), Standard length (SL), Pectoral fin length (LP), Ventral fin length (LV), Cephalic length (LC), Maxillary length (LM), Pre-orbital distance (POD1), 1st Dorsal fin length (LD1), 2nd Dorsal fin length (LD2), Eye diameter (O), Post-orbital distance (POD2), Anal fin length (LA), Caudal peduncle minimal depth (T), Maximum body height (TPC), Pre-ventral fin distance (PVD1), Post-anal fin distance (PAD), Post ventral fin distance (PVD2). Figure 2. Morphometric measurements of the greater weever Trachinus draco adapted from Fischer et al. (1987).

Results and Discussion On the 15th April 2017, one female specimen of the greater weever, Trachinus draco measuring 44.69 cm in total length and weighting 885 g was captured by trawler operating in Oran Bay at 120 m depth. Species identification sheets (Fischer et al., 1987; Djabali et al., 1993) were used to identify the specimen of T. draco (Fig.3) where the body appear elongated and compressed. Small eyes located near the dorsal profile of the head; width of the interorbital space roughly equal to half the diameter of the eye; large oblique mouth, the maxillary extending beyond the posterior edge of the eye when the mouth is closed with villiform teeth. According to Fischer et al., (1987) T. draco has a strong venomous spine on the operculum, 2 spines on the anterodorsal edge of the orbit and another above the upper lip, in front of the eye. Two dorsal fins, the first short counting 5 to 7 spines, the second, long counting 29 to 32 soft rays; anal with 2 Figure 3. Trachinus draco (44.69 cm TL ♀) caught in Oran Bay, spines and 29 to 32 soft rays. Generally, the greater weever is (Photographed by: ADDA NEGGAZ Hichem). greenish brown back with dark spots on the head, yellowish- white flanks according to the oblique rows of scales, of brown, blue, yellow lines; second dorsal fin yellowish, anal mauve.

Aquat Res 4(1), 55-64 (2021) • https://doi.org/10.3153/AR21005 Short Communication

Measurements, meristic characteristics, weight and percent- The maximum length ever recorded of T. draco belongs to age of each body part of the greater weever caught in Oran Bay re- IGFA 2001 in the Atlantic Ocean (Canary island, 56cm) and ported to total length are given in (Table 1). by Otel (2007) in Danube Delta (53cm) followed by Fischer et al., 1987 (45cm) in the Mediterranean, all successive rec- Table 1. Morphometric measurements as percentage of total ords are shown in Table 2. length (% TL) of Trachinus draco caught in Oran Bay (W. Mediterranean Sea). Greater Weever is caught as bycatch in the majority of fisheries and landings are declared from the following FAO re- Morphometric characteristics Measurement Proportion gions: Northeast Atlantic, Mediterranean and Black Sea. The (cm) (%) Total length (TL) 44.69 100.00 overall trend in landings is one of dramatic fluctuations with Fork length (FL) 43.44 97.20 a general increase in landings over time (Carpenter et al., Standard length (SL) 39.30 87.94 2015). As stated previously little is known on its ecobiology, Pectoral fin length (LP) 5.76 12.90 population trends and most of studies focused on its toxins. Ventral fin length (LV) 3.28 7.360 1st dorsal fin length (LD1) 2.74 6.140 In the Mediterranean Sea, the maximum length of T. draco 2nd dorsal fin length (LD2) 19.76 44.22 were reported as 45 cm TL (n=1124); 36 cm from Black Sea Cephalic length (LC) 7.67 17.16 (Fischer et al.,1987); If we consider to maximum length rec- Maxillary length (LM) 1.41 3.160 orded during our study so this length represents the maximum Post-orbital distance (POD1) 2.96 6.620 length for both Algerian and Western Mediterranean Sea. The Eye diameter (O) 0.77 1.720 aim of this paper is to present a compilation of maximum Post-orbital distance (POD2) 5.68 12.72 length for T. draco with a new record for the greater weever Pre-ventral fin distance (PVD1) 6.15 13.78 caught in Western Mediterranean Sea (Oran Bay). Post-ventral fin distance (PVD2) 2.70 6.060 Anal fin length (LA) 25.70 57.51 Wootton 1990; 1999 in Helfman et al. (2009) stated that fac- Post-anal fin distance (PAD) 2.66 5.950 tors such as temperature, food availability, nutrient availabil- Maximum body height (TPC) 2.57 5.750 ity, light regime, oxygen, salinity, pollutants, current speed, Caudal peduncle minimal depth (T) 8.40 18.80 predator density, intraspecific social interactions, and genet- Total weight (TW) 0.88 - ics often working in combination, creating large variations in Meristic characteristics size of fishes of the same and different ages, also populations Operculum spines 2* exposed to high fishing mortality/pressure will respond by re- Short eye spines 2 producing at smaller average sizes and ages. Generally, in the st 1 dorsal fin spines 7 (2*+5) Mediterranean and Black Sea where fishing activity is inten- nd 2 dorsal fin 32 sive, the maximum length was relatively low (Table 2) 32 cm Pelvic fin 6 in Tunisian waters, 38cm in French waters, 32.9 in Greek wa- Pectoral fins 15 ters, 23 cm in Egyptian waters cm TL. Anal fin 31 Contrarily, in oceanic and northern seawaters individuals Caudal fin 16 doesn’t face the same fishing pressure, maximum length ap- *: venomous pears more important with a maximal length recorded in Ca- According to Portillo Strempel et al., 2008 T. draco showed nary Islands reaching 56 cm (IGFA, 2001). In this context, a seasonal migratory behavior, with a preference for shal- frequenting the eastern part of oranian shoreline an area un- lower waters, up to 75 m depth during autumn and for deeper dergoing a less fishing pressure than the western area (Oran waters up to 160 m depth, during spring in the northern Al- Bay) (Pers.obs) we can explain that our specimen may have boran Sea (SW Mediterranean) which is the case of our spec- reached this maximum length observed. Also, we can add the imen captured in April 2017. fact that there is no predator known for T. draco at the top of the trophic chain.

Aquat Res 4(1), 55-64 (2021) • https://doi.org/10.3153/AR21005 Short Communication

Table 2. Maximum length records of Trachinus draco given by several authors.

Location Depth (m) TL (cm) TW (g) References Aegean Sea <30 35.2 235.82* Karakulak et al., (2006) Saros Bay 28-370 37.0 427.00 Ismen et al., (2007) Izmir Bay - 34.1 288.99* Ozaydin et al., (2007) N. Eastern Mediterranean 5-100 20.0 53.18 Sangun et al., (2007) Aegean Sea 30-70 36.6 365.42* Ilkyaz et al., (2008) Aegean Sea - 36.6 401.43 Kınacigil et al., (2008) Turkey Eastern Black Sea 60 35.0 549.20 Ak et al., (2009) İskenderun Bay 18-19m 20.6 55.84 Gökçe et al., (2010) Eastern Black Sea 60 25.8 131.76 Ak and Genç, (2013) 28.7 M 145.21 Iskenderun Bay - Buz and Basusta, (2015) 32.0 F 237.48 Aegean Sea 0-400 36.4 294.00 Öztekin et al., (2016) Black Sea - 40 - Bănărescu, (1964) Romania Agigea Eforie Nord Area 9.3-12.5 16.5 18-27 Roșca et al., (2010) Danube Delta - 53.0 - Otel, (2007) Tunisia Gulf of Tunis - 32.0 236.30 Hamed and Chakroun-Marzouk, (2016) Gulf of Gascogne - 38.5 317.97* Dorel, (1986) France Catalan coast 1-80 38.5 375.00 Crec’hriou et al., (2012) Cyclades, Aegean Sea 4-90 32.5 Erzini et al., (1999) Greece, Aegean Sea - 32.0 219.03* Moutopoulos and Stergiou, (2002) Greece Greece, Thermaikos Gulf - 30.5 189.37* Karachle and Stergiou, (2008) Greece North Aegean Sea 15-800 28.8 149.40 Torres et al., (2012) Korinthiakos Gulf 50-300 32.9 206.13* Moutopoulos et al., (2013) 40-80 24.2 83.90* Merella et al., (1997) Balearic Islands 0.5-1713 26.5 125.00 Morey et al., (2003) Spain - 34.0 259.64* Garmon, (2005) Eastern Atlantic <20 29.5 167.94* Mata et al., (2008) Alboan Sea 50-164 39.0 - Portillo Strempel et al., (2008) Eastern Atlantic Ocean 13-55 34.0 502.06* Gonçalves et al., (1997) Portugal Algarve coast - 39.6 554.10 Santos et al., (2002) Eastern Atlantic 30-350 39.0 460.00 Mendes et al., (2004) Egypt Alexandria Bay 30-200 23.0 200.52* Abdallah et al., (2002) Croatia Eastern Adriatic - 26.8 330.00 Dulčić and Kraljević, (1996) Italy Sicily 10-200 29.5 169.26* Giacalone et al., (2010) Schull Bay - 42.0 510.00 Went, (1973) Ireland Keem Bay (Co Mayo) - 35.4 311.00 Quigley et al., (1990) Ballycotton Bay (Co Mayo) - 38.7 - Quigley et al., (1994) North East Atlantic 35.0 344.00 Coull et al., (1989) North Sea/North-East Atlantic - 36.5 352.78* Wilhelms, (2013) - Western Atlantic, Canary island - 56.0 1740.00 IGFA, (2001) Northern/Central Adriatic - 32.8 - Custovic et al., (2014) 32.5 M 221.40 Denmark Kattegat 9.9-27.1 Bagge, (2004) 37.6 F 350.20 Mediterranean Sea 45.0 - - - Fischer et al., (1987) Black Sea 36.0 Algeria Oran Bay 120 44.69 885.00 Present study *Weight calculated from LWR (length weight relationship).

Aquat Res 4(1), 55-64 (2021) • https://doi.org/10.3153/AR21005 Short Communication

Conclusion Allen, K. R. (1971). Relation between production and biomass. Journal of the Fisheries Research Board of Canada, As conclusion, more efforts and means must be deployed to 28, 1573-1581. explore Oran Bay biodiversity deeply, target large specimens https://doi.org/10.1139/f71-236 and try to study fish population’s dynamics and their interac-

tion with different biotopes present in the area (sandy, Azizi, R., Rangel, L.F., Castro, R., Santos, M.J., Bahri, S. muddy, rocky, gravelly). (2016). Morphology, seasonality and phylogeny of Zschokkella trachini n. sp. (Myxozoa, Myxosporea) infecting Compliance with Ethical Standard the gallbladder of greater weever Trachinus draco (L.) from Conflict of interests: The authors declare that for this article they Tunisian waters. Parasitology Research, 115(11), 4129- have no actual, potential or perceived conflict of interests. 4138. https://doi.org/10.1007/s00436-016-5187-y Ethics committee approval: Ethics committee approval is not required for this study. Bagge, O. (2004). The biology of the greater weever (Trachi- Funding disclosure: - nus draco) in the commercial fishery of the Kattegat. ICES Acknowledgments: - Journal of Marine Science, 61(6), 933-943. Disclosure: - https://doi.org/10.1016/j.icesjms.2004.07.020

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64 AQUATIC RESEARCH

E-ISSN 2618-6365

Aquat Res 4(1), 65-72 (2021) • https://doi.org/10.3153/AR21006 Short Communication

Diagnosis of Aeromonas sobria and Saprolegnia sp. co-infection in rainbow trout fry (Oncorhynchus mykiss)

Remziye Eda YARDIMCI , Emre TURGAY

Cite this article as: Yardımcı, R.E., Turgay, E. (2021). Diagnosis of Aeromonas sobria and Saprolegnia sp. co-infection in rainbow trout fry (Oncorhynchus mykiss). Aquatic Research, 4(1), 65-72. https://doi.org/10.3153/AR21006

Istanbul University, Faculty of Aquatic ABSTRACT Sciences, Department of Aquaculture and Fish Diseases, Istanbul, Turkey The aim of the study was to determine a considerable level of mortalities occurred in rainbow trout fry (Oncorhynchus mykiss) cultured in a research hatchery located in Marmara Region/Turkey. Totally 18 individuals (1-8 g) were investigated by using bacteriological and mycological methods. The affected fish showed skin darkening, prolapses and fungal mats at the base of the fins. ORCID IDs of the author(s): According to morphological and biochemical characteristics of the isolates, all of them were iden- R.E.Y. 0000-0001-7737-8739 tified as Aeromonas sobria. Saprolegnia sp. was also observed in squash preparations of the skin. E.T. 0000-0001-9964-3919 All isolates were determined to be sensitive against florfenicol, enrofloxacin and ciprofloxacin. Histopathologically, vacuolar degeneration, haemorrhage and hyperaemia in the liver, tubular necrosis, periglomerular edema, and multifocal melanomacrophage deposits in the kidney and depletion of white pulp in the spleen were determined. Distal type epithelial cells hyperplasia was also observed in the gills. In diseased fish, motile Aeromonad septicaemia was described and Submitted: 16.06.2020 Saprolegnia sp. was also detected in fins and skin lesions but it was considered to be a secondary infection. Revision requested: 28.08.2020 Last revision received: 27.10.2020 Keywords: Rainbow trout fry, Oncorhynchus mykiss, Aeromonas sobria, Saprolegnia sp. Accepted: 30.10.2020 Published online: 26.11.2020

Correspondence: Remziye Eda YARDIMCI E-mail: [email protected]

Available online at http://aquatres.scientificwebjournals.com

Aquat Res 4(1), 65-72 (2021) • https://doi.org/10.3153/AR21006 Short Communication

Introduction Aquaculture activities have begun in Turkey in 1970s with or parasitic infections (Roberts, 2012). The present study rainbow trout (Oncorhynchus mykiss). Production of rainbow aimed to determine the cause of mortalities in rainbow trout trout reached to 103.192 t in 2018 in Turkey. In this period of fry (Oncorhynchus mykiss) cultured in a research hatchery of time, by the increase of the number of fish farms and the pro- Marmara Region in Turkey. duction, disease problems has begun and until recently, these Material and Methods epizootics have increased rapidly parallel to the epizootics in other countries. Bacteriological and Fungal Examination Motile Aeromonas septicaemia (MAS, Bacterial hemorrhagic Totally 18 moribund individuals were investigated by using septicemia, Aeromonad septicemia or Red Pest) caused by basic bacteriological and mycological methods. Samples motile members of the genus Aeromonas is a ubiquitous dis- were taken from internal organs and streaked onto Tryptic ease affecting freshwater and marine fish all over the world. Soy Agar and Sabouraud %2 Dextrose Agar and incubated at Fish pathogenic motile Aeromonads have often been associ- 22°C for 48-72h. After incubation, the isolated bacterial pure ated with A. hydrophila (Austin and Austin, 2007). However, cultures were examined using standard protocols according other members of the genus including A. sobria (Toranzo et to Austin and Austin (2007) and Buller (2004). Also rapid al., 1989), A. allosaccharophila (Martinez‐Murcia et al., diagnosis kit API 20E was used in all isolates. Before nec- 1992), A. caviae (Candan et al., 1995), A. jandaei (Esteve et ropsy, scrapings taken from fungal mats at the base of fins al., 1995), A. veronii biovar sobria (Rahman et al., 2002) and were stained with lacto-phenol cotton blue and examined un- A. schubertii (Alvarez et al., 2004) have also been detected as der light microscope. fish pathogens. These bacteria are known to cause various in- Antimicrobial Susceptibility Testing fections, especially gastroenteritis, by passing from animals to humans through food (Plumb and Hanson, 2011). All bacterial isolates were tested for antimicrobial susceptibility by using Kirby-Bauer disc diffusion method and per- Aeromonas sobria has been recognized as a fish pathogen formed using multidiscs (chloramphenicol, florfenicol, eryth- since 1987 and it was first reported in wild gizzard shad romycin, oxytetracycline, kanamycin, streptomycin, ampicil- (Dorosoma cepedianum) in USA (Toranzo et al., 1989). In lin, enrofloxacin, ciprofloxacin and flumequine). Isolates Turkey, A. sobria was first reported in intestinal tracts of were streaked onto Mueller-Hinton agar (Oxoid), incubated healthy Atlantic salmons (Salmo salar) in Black Sea (Kara- at 22°C for 48h and interpreted according to Clinical and La- tas, 1996). This pathogen was also detected in rainbow trout boratory Standards Institute (CLSI) data (CLSI, 2013). (Oncorhynchus mykiss) (Kayis et al., 2009; Ozer et al., 2009; Durmaz and Turk, 2009; Onuk et al., 2017), gold fish Histological Examination (Carassius auratus) (Korun and Toprak, 2007), green terror Histopathological tissue samples from the internal organs (Andinoacara rivulatus) (Şahin et al., 2019), gilthead sea were taken and fixed in 10% buffered formalin, processed bream (Sparus aurata) and sea bass (Dicentrarchus labrax) with routine methods and embedded in paraffin blocks. Sec- (Avsever et al., 2012) in Turkey. Wahli et al. (2005) declared tions (5μm) were stained with haematoxylin-eosin (HE) that A. sobria is a causative agent of ulcerative skin diseases (Culling, 1963) and examined under light microscope using in farmed perch (Perca fluviatilis L.) with high mortality in the image analysis system NIS-Elements BR Microscope Im- Switzerland. A. sobria caused mass mortality of Garra rufa aging Software (Nikon Instruments). in a hatchery in Slovakia (Majtan et al., 2012). Motile Aeromonas septicaemia are usually associated with Results and Discussion stressors (Shoemaker et al., 2015). Poor feeding response, The moribund fish samples externally showed loss of color lethargy, pale gills, exophthalmia, and haemorhagic eyes are or darkening of the skin (Figure 1A, B), eroded fins and fun- the most common clinical findings of MAS. Scale loss, gal mats at the base of fins (Figure 1B), slight exophthalmia frayed fins and necrotic lesions on the skin and friable organ (Figure 1C) and prolapse (Figure 1D). Internally, pale liver are also observed (Toranzo et al., 1989; Karatas, 1996; and visceral fat and accumulation of a mucoid yellowish fluid Yardımcı and Aydın, 2011; Shoemaker et al., 2015). in the intestines were observed (Figure 1E). Petechial haem- Infection of eggs, fry and larger fish by water mould is an- orrhage in the liver and splenomegaly were detected in a few other problem in cultured rainbow trout. Fungal infections sample (Figure 1F). These clinical findings are similar to the can occur as a secondary infection alongside bacterial, viral typical MAS findings reported by many researchers (Snieszko and Bullock, 1965; Toranzo et al., 1989; Karatas,

Aquat Res 4(1), 65-72 (2021) • https://doi.org/10.3153/AR21006 Short Communication

1996; Yardımcı and Aydın, 2011; Shoemaker et al., 2015). In Oomycetes of the genus Saprolegnia, especially S. parasit- MAS, outbreaks are associated with poor management and ica, are economically important pathogens of fish. Sapro- environmental status and this stress-related situation causes legnia species also affect to decline of the amphibians and mortality (Plumb and Hanson, 2011). In this study, a consid- crustaceans. In Japan, S. parasitica and S. diclina caused high erable level of mortalities occurred in the hatchery fish mortality of cultured rainbow, coho salmon (Oncorhynchus stocks. kisutch) and ayu (Plecoglossus altivelis) (Yuasa et al., 1977; Yuasa and Hatai, 1995). Grey-white patches on fish skin hav- Total of twenty Gram-negative motile isolates were recov- ing cotton-like appearance underwater were also observed in ered from kidney, spleen, liver and blood of ten moribund fish some rainbow trout fries. When fungal mats that stained with samples. These motile Gram-negative short rods produced lacto-phenol cotton blue were examined under light micro- white-cream convex colonies on Tryptic Soy Agar at 22°C scope, Saprolegnia sp. observed in fins and skin lesions. No after 48h. All isolates showed the same biochemical, morpho- growth was detected on Sabouraud %2 Dextrose Agar after logical characteristics and API 20E results. The bacterium the incubation at 22°C after 72h. For this reason, Saprolegnia produces arginine dihydrolase, catalase, β-galactosidase, in- infection was considered as a secondary, opportunistic infec- dole, lysine decarboxylase and oxidase but does not hydro- tion. lyse esculin. The API 20E profile is so similar with previous A. hydrophila reports (Buller, 2004; Austin and Austin, Durmaz and Türk (2009) reported that Aeromonas so- 2007). They were characterized by haemolytic colonies on bria isolates were highly resistant to oxytetracycline, strepto- sheep blood agar when grown at 25°C and 30°C and all of mycin and carbenicillin in their study. Onuk et. al (2017) re- them were identified as Aeromonas sobria (Table 1). ported that A. sobria strains, that were isolated from rainbow trout, from mullet and in water resources from different geo- Table 1. Some phenotypic and morphological characteristics graphic regions of Turkey, were gentamicin-sensitive but re- of Aeromonas sobria isolates sistant to beta-lactam antibiotics and ampicillin. In this study, Characteristics A. sobria n=20 all isolates were found to be susceptible to florfenicol, en- Colony colour Cream rofloxacin and ciprofloxacin, while they were semi-sensitive Morphology Rods to chloramphenicol and flumequin, and resistant to erythro- Gram Staining - mycin, oxytetracycline, kanamycin, streptomycin, ampicillin Motility + and vibriostatic agent O/129. Similar sensitivity to ciprofloxacin and enrofloxacin were reported by other research- Cytochrome Oxidase + ers (Guz and Kozinska, 2004; Durmaz and Turk, 2009; Onuk Catalase + et al., 2017; Şahin et al., 2019). We found that the highest O/F Test +/+ resistance was against ampicillin and oxytetracycline. While Inositol - ampicillin is used for the treatment of human diseases, oxy- Arabinose - tetracycline is used in the treatment of bacterial diseases in Sorbitol - freshwater fish farming in Turkey. The possible cause of re- Esculin - sistance to these antibiotics is thought to be due to the heavy use of these antibiotics. Production of H2S - Citrate + Histopathologically, vacuolar degeneration and necrosis in ONPG + the parenchyma cells of liver, hyperaemia and haemorrhage 0/129 (150µg) R in the liver (Figure 2A, B), depletion of the spleen (Figure Indole + 2C), myopathy (Figure 2D), tubular necrosis, periglomerular edema and multifocal melanomacrophage centers in the kid- Methyl Red V ney (Figure 2E), hyperplasia of gill lamellae and disruption Voges-Proskauer Test + of gill epithelium (Figure 2F) and depletion of white pulp in Arginine + the spleen were determined. Our histopathological results are Lysine - similar with previously reported histopathological findings of Ornithine - Motile Aeromonad infections (Yardımcı and Aydın, 2011; API 20E results 7 2 4 7 1 3 7 5 7 Laith and Najiah 2013; Saharia et al., 2018). +: positive reaction, -: negative reaction, R: resistant, V: variable

Aquat Res 4(1), 65-72 (2021) • https://doi.org/10.3153/AR21006 Short Communication

Figure 1. Moribund fish showed (A) depigmentation of the skin, (B) eroded fins and fungal mats at the base of fins (*), (C) slight exophthalmia (arrowed), (D) haemorrhage and prolapse (arrowed), (E) visceral fat (*) and (F) splenomegaly(*).

Aquat Res 4(1), 65-72 (2021) • https://doi.org/10.3153/AR21006 Short Communication

Figure 2. Photomicrographs of the tissue sections of moribund rainbow trout fries. (A) Vacuolar degeneration and necrosis in the parenchyma cells of liver, hyperaemia and haemorrhage in the liver H&E X20, (B) necrosis in the parenchyma cells of liver and haemorrhage H&E X20, (C) depletion of white pulp in the spleen H&E X20, (D) myopathy H&E X10, (E) tubular necrosis (n), periglomerular edema (*) and multifocal melanomacrophage centers (mc) in the kidney H&E X20, (F) hyperplasia of the gill lamellae (arrowed) and disruption of the gill epithelium (*) H&E X20.

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A co-infection caused by Saprolegnia parasitica and Aer- Buller, N.B. (2004). Bacteria from Fish and Other Aquatic omonas hydrophila were described previously in sea bass by Animals: A Practical Identification Manuel. CABI Publish- Dinçtürk et al. (2018) in a recirculating aquaculture system ing, Cambridge USA, ISBN 0851997384. and they suggested that S. parasitica could be dominant in the https://doi.org/10.1079/9780851997384.0000 outbreak, but in our case we found that Aeromonas sobria was the primary cause. Candan, A., Kucuker, M.A., Karatas, S. (1995). Motile aeromonad septicaemia in Salmo salar cultured in the Black Conclusion Sea in Turkey. Bulletin of the European Association of Fish In aquaculture, increased production, pressures on faster Pathologists, 15(6), 195-196. growth, high stock density could create conditions conducive to outbreak of bacterial infectious diseases. In conclusion, CLSI, (2013). Performance Standards for Antimicrobial Sus- motile Aeromonad septicaemia was described in this study. ceptibility 23th informational supplement. CLSI Document Saprophytic fungus Saprolegnia sp. played a role as a sec- M100- S23, (ISBN1-56238-865-7-Print:1-56238-866-5– ondary pathogen in this infection. In addition, according to Electronic) Clinical and Laboratory Standards Institute, 950 the data obtained from this study, enrofloxacin was success- West Valley Road, Suite 2500, Wayne, Pennsylvania, 19087 ful with a feed dose of 20 g / 10 kg / 7-8 days in the treatment USA. of diseased fish. Culling, C.F.A. (1963). Handbook of Histopathological Techniques. Second edition, Butterworth & Co. Compliance with Ethical Standard Conflict of interests: The authors declare that for this article they Dinçtürk, E., Tanrıkul, T.T., Türk Çulha, S. (2018). Fun- have no actual, potential or perceived conflict of interests. gal and Bacterial Co-Infection of Sea Bass (Dicentrarchus Ethics committee approval: This study was approved by Istanbul labrax, Linnaeus 1758) in a Recirculating Aquaculture Sys- University Local Committee on Animal Research Ethics (Decision tem: Saprolegnia parasitica and Aeromonas hydrophila. year 2013/ number 70) and conducted in accordance with ethics Aquatic Sciences and Engineering, 33(3), 67-71. committee procedures of animal examination. https://doi.org/10.26650/ASE201811

Funding disclosure: This work was supported by the Scientific Re- search Projects Coordination Unit of Istanbul University Project Durmaz, Y., Türk, N. (2009). Alabalık işletmelerinden mo- number: 35964. til aeromonasların izolasyonu ve antibiyotiklere duy- arlılıklarının saptanması. Kafkas Üniversitesi Veteriner Acknowledgments: We thank Prof. Dr. Süheyla KARATAŞ for Fakültesi Dergisi, 15 (3): 357-361. her comments. Disclosure: - Esteve, C., Amaro C., Garay, E., Santos, I., Toranzo, A.E. (1995). Pathogenicity of live bacteria and extracellular prod- References ucts of motile Aeromonas isolated from eels. Journal of Ap- plied Microbiology, 78(5), 555-562. Alvarez, R.J.D., Agurto, C.P., Alvarez, A.M., Obregon, J. https://doi.org/10.1111/j.1365-2672.1995.tb03099.x (2004). Resistencia Antimicrobiana en Bacterias Aisladas de

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Korun, J., Toprak, B.H. (2007). Japon (Carassius auratus) Roberts, R.J. (2012). Fish Pathology. 4.Edition. Blackwell balıklarından izole ve identifiye edilen Aeromonas hydroph- Publishing, United Kingdom, pp.387-390 ISBN: 978-1-118- ila, A. caviae ve A. sobria türlerinin antibiyotik hassasiyetleri, 22296-6 hemolitik aktiviteleri ve siderofor üretimleri üzerine bir https://doi.org/10.1002/9781118222942 çalışma. Türk Sucul Yasam Dergisi, 3(5), 776-782. Saharia, P., Pokhrel, H., Kalita, B., Hussain, I.A., Islam, Laith, A.R., Najiah, M. (2013). Aeromonas hydrophila: an- S.(2018). Histopathological changes in Indian Major Carp, timicrobial susceptibility and histopathology of isolates from Labeo rohita (Hamilton), experimentally infected with Aer- diseased catfish, Clarias gariepinus (Burchell). Journal of omonas hydrophila associated with hemorrhagic septicemia Aquaculture Research & Development, 5(2), 1-7. of Central Brahmaputra valley of Assam, India. Journal of Entomology and Zoology Studies, 6(5), 06-11 Majtan, J., Cerny, J., Ofukana, A., Takac, P., Kozanek, M. (2012). Mortality of therapeutic fish Garra rufa caused Shoemaker, C., Xu, D., Lafrentz, B., Lapatra, S. (2015). by Aeromonas sobria. Asian Pacific Journal of Tropical Bi- Overview of Fish Immune System and Infectious Diseases. omedicine, 2(2), 85-7. P1-24, In: Dietary Nutrients, Additives, and Fish Health (Ed: https://doi.org/10.1016/S2221-1691(11)60197-4 Cheng-Sheng Lee , Chhorn Lim, Delbert M. Gatlin II, and Carl D. Webster). Published by JohnWiley & Sons, Inc., Ho- Martinez-Murcia, A.J., Esteve, C., Garay, E., Collins, boken, New Jersey384p. ISBN: 10987654321. M.D. (1992). Aeromonas allosaccharophila sp. nov., a new https://doi.org/10.1002/9781119005568.ch1 mesophilic member of the genus Aeromonas. FEMS Micro- biology Letters, 91, 199-205. Snieszko, S.F., Bullock, G.L., (1965). Freshwater fish dis- https://doi.org/10.1111/j.1574-6968.1992.tb05209.x eases caused by bacteria belonging to the genera aeromonas and pseudomonas. U.S.A. Fish and wildlife service. Fishery Onuk, E.E., Çaycı Tanrıverdi, Y., Çoban, A.Y., Çiftçi, A., Icaflet No.459. Balta, F., Didinen, B.I., Altın, S. (2017). Balık ve yetiştirme suyu kökenli Aeromonas izolatlarının antimikrobiyal duy- Şahin, A.G., San, A.T., Gürçay, S., Alkan, S.M. (2019). arlılıklarının saptanması. Ankara Üniversitesi Veteriner Determination of antibiotic resistance sensitivity of Aer- Fakültesi Dergisi, 64, 69-73. omonas sobria isolated from Green terror (Andinoacara riv- https://doi.org/10.1501/Vetfak_0000002777 ulatus). Ege Journal of Fisheries and Aquatic Sciences, 36(3), 265-269. Ozer, S., Bulduklu, P., Tezcan, S., Dönmez, E., Aydin, E., https://doi.org/10.12714/egejfas.2019.36.3.07 Aslan, G., Emekdas, G. (2009). Genetic diversity and antimicrobial susceptibility of motile aeromonads isolated from Toranzo, A.E., Baya, A.M., Romalde, J.J. Hetrick, F.M. rainbow trout (Oncorhynchus mykiss, walbaum) farms. Jour- (1989). Association of Aeromonas sobria with mortalities of nal of Applied Ichthyology, 25 (2), 195-200. adult gizzard shad, Dorosoma cepedianum lesueur. Journal https://doi.org/10.1111/j.1439-0426.2008.01222.x of Fish Diseases, 12, 439-448. https://doi.org/10.1111/j.1365-2761.1989.tb00555.x Plumb, J.A., Hanson, L.A. (2011). Health Maintenance and Principal Microbial Diseases of Cultured Fishes. 3rd edn. TUİK (2019). http://www.tuik.gov.tr/PreHaberBulten- Ames, IA: Wiley-Blackwell, 492 pp. leri.do?id=30697 Türkiye İstatistik Kurumu (accessed: 12.06.2019). Rahman, M., Colque-Navarro, P., Kühn, I., Huys, G., Swings, J., Möllby, R. (2002). Identification and Character- Wahli, T., Burr, S.E., Pugovkin, D., Mueller, O., Frey, J. ization of Pathogenic Aeromonas veronii Biovar Sobria As- (2005). Aeromonas sobria, a causative agent of disease in sociated with Epizootic Ulcerative Syndrome in Fish in farmed perch, Perca fluviatilis L.. Journal of Fish Diseases, Bangladesh. Applied and Enviromental Microbiology, 68(2), 28(3), 141-150. 650-655. https://doi.org/10.1111/j.1365-2761.2005.00608.x https://doi.org/10.1128/AEM.68.2.650-655.2002 Yardımcı, B., Aydın, Y. (2011). Pathological findings of experimental Aeromonas hydrophila infection in Nile tilapia

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72 AQUATIC RESEARCH

E-ISSN 2618-6365

Aquat Res 4(1), 73-87 (2021) • https://doi.org/10.3153/AR21007 Review Article

Gıda güvenliği açısından su ürünlerinde mikroplastik riski ve araştırma yöntemleri

İdil CAN TUNÇELLİ , Nuray ERKAN

Cite this article as: Can Tunçelli, İ., Erkan, N. (2021). Gıda güvenliği açısından su ürünlerinde mikroplastik riski ve araştırma yöntemleri. Aquatic Research, 4(1), 73-87. https://doi.org/10.3153/AR21007

İstanbul Üniversitesi, Su Bilimleri ÖZ Fakültesi, Balıkçılık ve Su Ürünleri İşleme Teknolojisi Bölümü, İstanbul, Son yıllarda artan plastik kullanımı ve yanlış geri dönüşüm politikaları ekosistemde plastik atıkların birikme- Türkiye sine neden olmuştur. Sucul ekosistemdeki canlılar üzerindeki etkilerinin görülmesiyle birlikte plastik kirliliği küresel bir sorun haline gelmiştir. Ortamda farklı fiziksel, kimyasal ve biyolojik etkenlerden dolayı mikroplastiklere (MP’lere) ve nanoplastiklere (NP’lere) parçalanan plastikler, besin zincirine girerek insan sağlı- ğını tehdit etmektedir. Yaygın plastik kirliliğinin bir sonucu olarak, mikroplastikler ve nanoplastikler zoo- planktonlardan, balıklara, kabuklu su ürünlerinden deniz memelilerine kadar birçok farklı canlı tarafından yutulmaktadır. Su ürünlerinin bünyelerine giren mikroplastikler canlı dokuda sindirilip, doku ve organlar ORCID IDs of the author(s): arasında yer değiştirebilmektedir. Bununla birlikte su ürünleri işleme teknolojilerinde yer alan bazı aşamalar İ.C.T. 0000-0002-9999-6658 da mikroplastik kontaminasyon kaynağı olabilmektedir. Mikroplastiklerin neden olduğu fiziksel, kimyasal N.E. 0000-0002-0752-8495 ve biyolojik toksisite etkileri henüz tam olarak bilinmemektedir. İleride yapılacak olan çalışmalarda, tüketici sağlığı açısından işlenmiş su ürünlerindeki mikroplastiklerin kaynağının ve bulaşma yollarının incelenip belirlenmesi önem arz etmektedir. Bu derlemede, sucul ekosistemlerden besin zincirine giren mikroplastiklerin gıda güvenliği açısından işlenmiş ürünlerdeki riskleri tartışılıp, bu araştırma alanındaki mikroplastiklerin identifikasyonu ve sayımı için analitik yöntemler incelenmiştir. Submitted: 26.10.2020 Anahtar Kelimeleri: Plastik kirliliği, Nanoplastik, Kontaminasyon, İşleme teknolojileri, FTIR, Raman Revision requested 06.11.2020 Last revision received 17.11.2020 ABSTRACT Accepted: 17.11.2020 Microplastic risks in the seafood in terms of food safety and their research methods Published online: 02.12.2020 Plastic waste has accumulated in the aquatic ecosystem as a result of the increasing use of plastic in recent years and their wrong recycling policies. Plastic pollution has become a global problem with its effects on aquatic organisms. Plastics that break down into microplastics (MPs) and nanoplastics (NPs) due to different physical, chemical and biological factors in the environment enter the food chain and directly threaten human Correspondence: İdil CAN TUNÇELLİ health. As a result of widespread plastic pollution, microplastics and nanoplastics are ingested by many dif- E-mail: [email protected] ferent species, from zooplankton, fish, shellfish to marine mammals. Microplastics that enter into marine organisms can move within living tissue and move between tissue and organ. However, some stages in seafood processing technologies can also be a source of microplastic contamination. Physical, chemical and biological toxicity effects caused by microplastics are not fully known yet. In future studies, it is important to examine and determine the source and transmission routes of microplastics in seafood for consumer health. In this review, the risks of microplastics entering the food chain from aquatic ecosystems in seafood products

in terms of food safety are discussed, and analytical methods for the identification and extraction of micro- © 2021 The Author(s) plastics in this research area are examined. Keywords: Plastic pollution, Nanoplastics, Contamination, Seafood processing technologies, FTIR, Raman Available online at http://aquatres.scientificwebjournals.com

Aquat Res 4(1), 73-87 (2021) • https://doi.org/10.3153/AR21007 Review Article

Giriş Günümüz toplumunda plastik, düşük yoğunlukları, çok geniş işlemler sonucu mikroplastiklere parçalanmaktadırlar. Parça- bir sıcaklık aralığında kullanılabilirlikleri, kimyasallara ve lanan bu materyaller rüzgar ve akıntı yardımıyla uzun mesa- ışığa karşı dirençli olmaları, kolayca işlenebilir özellikte ol- felere taşınıp, kökenlerinden çok uzaklardaki ortamlarda bi- maları ve nispeten düşük maliyetleriyle günlük yaşamın vaz- rikebilmektedirler (Barnes ve diğ., 2009). geçilmez bir parçası haline gelmiştir (Ryan, 2015). Ondoku- zuncu yüzyılın başında termoplastiklerin gelişimiyle birlikte Mikroplastikler (MP'ler) genelde boyutu 5 mm'nin altındaki kullanım alanı oldukça geniş olan doğal ve sentetik polimer- polimerik partiküller olarak tanımlanmaktadır (GESAMP, ler üzerine araştırmalar başlamıştır. Plastiğin modern gelişimi 2015). EFSA (European Food Safety Authority: Avrupa Gıda ise yirminci yüzyılların başında en az 15 yeni polimer sınıfı- Güvenliği Otoritesi) (2016)’da yayınladığı raporda MP’leri nın sentezlenmesiyle genişlemeye başlamıştır (Andrady ve 5mm-100 nm arası olarak tanımlarken, 100 nm’den küçük Neal, 2009). Toplu plastik üretiminin başladığı 1930- polimerik parçaları nanoplastikler (NP'ler) olarak tanımlan- 1940'lardan bu yana, plastik üretim hacmi istikrarlı bir şe- mıştır. Bir başka tanımlamada ise 2,5 cm’den büyük parçalar kilde artmaktadır (Ryan, 2015). Günümüzde küresel plastik makroplastik (Galgani ve diğ., 2015), 500 μm–5 mm arası üretimi yıllık 359 milyon tona ulaşmıştır (PlasticsEurope, mezoplastik, 50–500 μm arası mikroplastik ve 50 μm’dan kü- 2019) ve öngörülebilir gelecekte sürekli hızlı bir büyüme ile çük parçalar ise nanoplastik olarak tanımlanmıştır (Ryan, artması beklenmektedir (Ryan, 2015). 2015). Literatürde çok sayıda farklı boyut temelli tanımı ya- pılmış olan bu maddelerin henüz yaygın, standartlaştırılmış Katlanarak artan plastik üretim hacmi, uygun olmayan şe- bir tanımı bulunmamaktadır (GESAMP, 2015; EFSA, 2016; kilde taşınan atık plastik miktarlarıyla birleşince tüm dünya Ašmonaitė, 2019). ekosistemini tehdit eden küresel bir sorun ortaya çıkmıştır (Barnes ve diğ., 2009; Ryan, 2015). Özellikle 1950'lerden bu Mikroplastik Kaynakları yana sanayinin gelişimiyle birlikte plastik malzemeler eko- Deniz kıyılarında, yüzeyinde ve tabanında biriken atıkların sistemdeki tüm ortamlarda kirlilik oluşturmakta ve içerisin- önemli bir kısmını plastik maddeler oluşturmaktadır. Plastik deki canlıları etkilemektedir (Cózar ve diğ., 2014). Plastik ve torbalar, balıkçılık malzemeleri, gıda ambalajları gibi sahil- neden olduğu etkiler tüm dünyada yüzey suları (Cincinelli ve lerde en yaygın bulunan öğeler, bulunan atıkların %80'inden diğ., 2019; Lorenz ve diğ., 2019), derin deniz sedimentleri fazlasını oluşturmaktadır (Galgani ve diğ., 2015). Bunun (Van Cauwenberghe ve diğ, 2013; Zhang ve diğ., 2020), am- yanı sıra MP’ler, büyük plastik ürünlerin üretiminde kullanı- fipodlar (Jamieson ve diğ., 2019), balıklar (Zhu ve diğ., lan peletler, granüller, lifler ve tozlar, kişisel bakım ürünle- 2019), çift kabuklular (Moreschi ve diğ., 2020); yumuşakça- rindeki mikro aşındırıcı partiküller, ilaçlar ve sentetik giysi- lar (Oliveira ve diğ., 2020), buzullar (Obbard ve diğ., 2014; lerin yıkanması sonucunda da doğrudan çevreye deşarj ola- Bergmann ve diğ., 2019), toprak (Scheurer ve Bigalke, 2018), bilmektedirler (Browne, 2015). hava ortamı (Dris ve diğ., 2017), deniz kuşları (Amélineau ve diğ., 2016) ve sofra tuzları (Gündoğdu, 2018) gibi farklı Geniş coğrafi ölçekleri aşarak kutuplardan tropik ve ılıman madde ve ortamlarda tespit edilmiştir. bölgelere kadar tüm ekosistemlerde görülen mikroplastik kir- liliğinin kaynakları, doğrudan kullanım için öğütülerek veya Plastikler, altısı "büyük altı" olarak da adlandırılan yirmiden ekstrüzyon ile parçalanan plastik partiküllerin oluşturduğu fazla polimer ailesini içerir: polipropilen (PP), yüksek ve dü- “birincil kaynaklar” ve daha büyük plastik materyalin çev- şük yoğunluklu polietilen (HDPE ve LDPE), polivinil klorür rede giderek daha küçük parçalara parçalanmasıyla oluştur- (PVC), poliüretan (PUR), polietilen tereftalat (PET), polisti- duğu “ikincil kaynaklar” şeklinde ikiye ayrılmaktadır. Birin- ren (PS) ve bu polimerler Avrupa'daki plastik üretiminin % cil kaynaklı MP’ler, lastiklerin aşınması veya yıkama sıra- 80'ine karşılık gelmektedir (Dehaut ve diğ., 2016; Andrady sında sentetik tekstillerin aşınması gibi üretim, kullanım veya ve Rajapakse, 2019; PlasticsEurope, 2019). Şu anda üretilen bakım sırasında büyük plastik nesnelerin aşınmasından da plastiklerin çoğu fosil yakıt bazlı malzemelerdir ve küresel kaynaklanabilirler (Browne, 2015; Boucher ve Friot, 2017; olarak mevcut fosil yakıtın %4 kadarı ham plastik üretimi için Ašmonaitė, 2019). Deniz ortamındaki mikroplastiklerin kullanılmaktadır (Geyer ve diğ., 2017; Ašmonaitė, 2019). %69-81'i ikincil kaynaklı MP’lerden oluşmakta ve doğaya Günümüzde büyük bir sorun haline gelen aşırı plastik kulla- atılan tek kullanımlık plastiklerden, hayalet ağlara kadar ge- nımı ve bunların oluşturduğu atıklar sonucu özellikle sucul niş bir kapsamı bulunmaktadır (Boucher ve Friot, 2017; EU, ekosistemlere yoğun bir plastik partikül deşarjı söz konusu- 2017). dur (Galgani ve diğ., 2015). Okyanus gibi büyük su kitlele- Düşünülenin aksine plastik kirliliğine neden olan etmenlerin rine girdikten sonra plastik materyaller, mekanik ve biyolojik önemli ölçüde bir kısmı da içerisindeki materyalin özelliğine

Aquat Res 4(1), 73-87 (2021) • https://doi.org/10.3153/AR21007 Review Article

çok da dikkat edilmeyen ürünlerinden kaynaklanmaktadır; farklı şekilde kategorize edilmiştir; fotodegradasyon (UV ışık yıkama esnasında sentetik fiber salınımı yapan kumaşlı giy- gibi ışık veya fotonların etkisiyle), termal bozunma (yüksek siler, yollarda aşınan araba lastikleri, suya veya toprağa aşı- sıcaklıkla) termo-oksidatif bozunma (yavaş oksidatif bo- nım yapan gemi ve otoyol boya maddeleri ve mikroeksfoli- zunma veya orta sıcaklıklarda gerçekleşen moleküler bo- yant madde içeren kişisel kozmetik ürünleri bunlara örnektir zulma), hidroliz (su ile reaksiyon sonucu) ve biyolojik bo- (Boucher ve Friot, 2017). Örneğin, yapılan deneysel bir ça- zunma (organik materyallerin mikroorganizmalar tarafından lışmada, ev tipi çamaşır makinelerinden atık suya boşaltılan ayrıştırılması). Bu bozunma, polimer türü ve polimer yaşıyla elyaf sayısını incelenmiştir ve makinenin yıkama başına 1900 birlikte güneş ışığı, sıcaklık, yağmur, nem, ışınlama, pH, kir- adet elyaf suya salınım yaptığı sonucuna ulaşılmıştır. Bu ça- leticiler, termal döngüler ve oksijen içeriği gibi çevresel ko- lışma sonucunda deniz habitatlarında bulunan mikroplastik şullar dahil olmak üzere birçok farklı faktöre bağlıdır (Vee- liflerin büyük bir kısmının, giysilerin yıkanmasının bir so- rasingam ve diğ., 2020). nucu olarak suya bulaşabileceği düşünülmektedir (Browne, 2015). Rochman ve diğ. (2015), insan tüketimine sunulan ba- Özellikle sahillerde UV’ye ve oksidasyona maruz kalan plas- lık ve midyelerde tekstil kökenli MP’lerin varlığını bildirmiş- tiklerde bu süreç, daha yüksek sıcaklıktaki bölgelerde veya lerdir. fiziksel aşınmanın meydana geldiği yerlerde daha hızlı ol- maktadır. Plastik materyal tortu, toprağa gömüldüğünde veya MP’ler, okyanuslara girdikten sonra yüzme veya batma eği- su sütunu içerisinde parçalanmanın hızı önemli ölçüde azal- limindedir ve bir kısmı da okyanus akıntılarından kaynakla- maktadır (UNEP, 2015). Su, ışığın neden olduğu oksidatif nan girdaplarda birikmektedirler. Bu MP’lerin 93,000 ila bozunmayı baskıladığından, sudaki plastiğin bozunma hızı 268,000 tonunun (93-268 kilotonunun) şu anda okyanuslarda havadakinden veya kumsallardakinden çok daha yavaştır yüzdüğü tahmin edilmektedir (Boucher ve Friot, 2017). Yo- (Veerasingam ve diğ., 2020). ğunluklarına göre, örneğin polipropilen gibi deniz suyundan daha hafif MP’ler okyanuslarda yüzerek geniş bir alana dağı- MP'lerin boyutu çok küçük olduğundan, zooplankton, omur- lım gösterirken, akrilik gibi deniz suyundan daha yoğun gasızlar ve küçük balıklar tarafından yanlışlıkla yiyecek ola- MP’ler büyük olasılıkla okyanus tabanında birikerek nihaye- rak yutulabilmektedir (Veerasingam ve diğ., 2020) ve bu şe- tinde besin zincirlerine (Seltenrich, 2015) giriş yapmaktadır- kilde besin zincirine girmektedirler (GESAMP, 2015). Plas- lar (Boucher ve Friot, 2017). tikler genelde yapılarında stabilizatörler, plastikleştiriciler, alev geciktiriciler ve suya salınabilen pigmentler gibi bazı Mikroplastiklerin Sınıflandırılması katkı maddelerini de içermektedir (EU, 2017). İnsan sağlığı açısından en büyük endişelerden biri de gıda zincirinde biri- MP'ler tek tip mikrosferlerden, düzensiz şekilli plastik parça- ken MP’lerin içerisinde ortamdan emilen bazı toksik madde- lara, peletlere, mikroskobik liflere, köpüklere, filmlere ve fi- lerin taşınmasıdır (Ericksen ve diğ., 2014). Bu kimyasallar lamanlara kadar farklı şekillerde bulunmaktadır (Hidalgo- (katkı maddeleri) biyolojik dokulara sızarak, organizmalarda Ruz ve diğ., 2012). Genellikle birincil kaynaklı MP’ler, ikin- ve gıda zincirinde biyolojik birikim yapabilmektedirler. cil kaynaklı MP’lere göre daha düzenli ve tutarlı bir morfolo- Farklı su ve canlı ortamlarındaki MP’lerin polimerik bileşi- jiye sahiptirler (Boucher ve Friot, 2017). Kullanım amacına mini belirlemek için birçok analitik yöntem kullanılmaktadır göre farklılık içerebildiği için çok farklı renklerde üretilen (Veerasingam ve diğ., 2020). plastikler, siyah, şeffaf, kırmızı, mavi, beyaz, pembe, sarı, mor, turuncu, yeşil, kahverengi veya çok renkli şeklinde do- Besin Zincirine Mikro ve Nanoplastiklerin ğada bulunabilmektedir (Hidalgo-Ruz ve diğ., 2012). Girişi Plastiklerin Mikroplastiklere Bozunması Mikroplastikle kontamine olmuş gıda maddesi dışında, gıda- Doğaya bırakılan plastik parçacıklar zamanla farklı etmenler nın işlenmesi sırasında kullanılan teknik ekipman, katkı mad- sonucu daha küçük parçacıklara parçalanmaya ve bozulmaya deleri, işleme prosedürü sırasında kullanılan yardımcı ekip- devam etmektedir. Bozulma sonucunda yapıları değişen po- manlar, kullanılan ambalaj ve diğer dış kaynaklar ile konta- limerlerde, renk bozulması, yüzey çatlaması ve parçalanma mine olan gıdanın tüketimi besin zincirine mikro ve nano- gibi etkiler gözlemlenebilmektedir (UNEP, 2015). Bu parça- plastiklerin girişini açıklamaktadır. lanma biyolojik bozunma (mikroorganizmalar), kimyasal ay- rışma (UV ışınlar yardımıyla) veya fiziksel etkenler (dalga hareketi, rüzgar, aşındırıcı kum veya çökelti yardımıyla) nedeniyle oluşmaktadır (Barnes ve diğ., 2009; Hidalgo-Ruz ve diğ., 2012; Browne, 2015). MP'lerin bozunma süreçleri beş

Aquat Res 4(1), 73-87 (2021) • https://doi.org/10.3153/AR21007 Review Article

Mikroplastiklerin İşleme Teknolojileri Kaynaklı Bulaşması

Su Mikroplastiklerin Mikroplastiklerin Besin Mikroplastik İçeren Zincirine Girişi Tuz ve Kaynakları baharatlar Su Ürünleri Eldiven, Kuşlar bone, maske Deniz memelileri vb. Kesme tahtaları Tüketim +UV ve bıçaklar Deniz kaplumbağaları İşleme makinaları Kirleticiler Mikroplastikler Nanoplastikler

Fiziksel ve Biyolojik Balıklar Çözünme Eklem Yumuşakçalar bacaklılar

Ambalaj Zooplankton materyali

Kıyafet, önlük vb. Hava ve filtrasyon sistemi Şekil 1. Sucul canlılardan ve işleme proseslerinden kaynaklı insan tüketimine bulaşan mikroplastik ve nanoplastik riski Figure 1. Microplastic and nanoplastic contamination risks of human consumption due to aquatic species and seafood processing technologies

Aquat Res 4(1), 73-87 (2021) • https://doi.org/10.3153/AR21007 Review Article

Besin zincirine giren plastikler ve potansiyel zararlı etkileri Küresel su ürünleri tüketimi 2020 yılı itibariyle, tüketilen tüm son yıllarda hem su ürünleri hem de onları tüketen insanlar proteinin %7'sini ve hayvansal protein tüketiminin yaklaşık için tehlike oluşturmaktadır (Şekil 1). Plastikler sucul canlı- %17'sini temsil etmektedir. Tüketilen su ürünlerinin büyük ların hareket etmesine, nefes almasına ve beslenmesine engel bir kısmı avcılık yoluyla (96,4 milyon ton), diğer kısmı ise su olacak şekilde vücutlarına dolanabilir veya takılabilir. Diğer ürünleri yetiştiriciliği (82,1 milyon ton) yoluyla sofralara gel- bir yol ise plastiklerin canlılar tarafından yiyecek zannedilip mektedir (FAO, 2020). Su ürünleri yetiştiriciliğindeki canlı- yutulması yoluyla gerçekleşmektedir (Kühn ve diğ., 2015). ları, havuzlarda, tanklarda veya seçilmiş su kütlelerinde ye- tiştirerek çevresel koşullarını kontrol etmek mümkündür. Mikroplastiklerin besin zincirine girişi, kasıtlı veya yanlış- Yetiştiriciliği yapılan canlıların yaşam süresi genellikle do- lıkla yutulması sonucu ve ikincil kaynaklı sindirimi sonucu ğadan avlanan canlı türlerine kıyasla daha kısa olduğundan gerçekleşmektedir. MP’ler renkleri sebebiyle sucul canlılar zamanla MP birikimi açısından bunların tüketiminin daha az tarafından gıda zannedilip kasıtlı olarak tüketilmektedirler tehlikeli olduğu düşünülmektedir (Smith ve diğ., 2018). Lite- (Kühn ve diğ., 2015). ratürde yetiştiricilik ve avcılıktan elde edilen su ürünlerinin Kabuklu deniz canlıları, balıklar ve balinalar gibi bazı deniz mikroplastik içeriklerindeki farklılıklar ve kaynakları hak- memelileri suyu filtre ederek beslendiklerinden dolayı sudaki kında belirsizlik bulunmaktadır. Van Cauwenberghe ve Jans- MP’leri de yutmaya yatkındırlar. İkincil kaynaklı sindirim sen (2014), çiftlik midyelerinin, doğadan yakalanan midye- ise, canlıların, bünyesinde MP bulunduran diğer canlılar ile lerden (126 adet) önemli ölçüde daha yüksek miktarlarda MP beslendiğinde oluşan durumdur. Sudan zooplankterlere ve içeriğine (178 adet) sahip olduğunu bulmuşlardır. Ek olarak, daha sonra da balıklara kadar olan bu geçiş sonucu mikro- Rochman ve diğ. (2015) tarafından Endonezya ve ABD’deki nano plastikler (MNP’ler) yüksek trofik seviyelerde birikime pazarlarda ticari olarak satılan balık ve midyelerde mikrop- yol açabilmektedirler. Besin zincirinde ilerleyen MP’ler, su lastiklerin (>500 μm) varlığı bildirilmiştir (Rochman ve diğ., ürünleri tüketimi sonucu insanlara geçmektedir (GESAMP, 2015). 2015; Hantoro ve diğ., 2019). Bu durum insanlar için özel- Bununla birlikte su ürünleri sektörünün yan ürünü olarak üre- likle bütün olarak tüketilen kabuklu su ürünlerini ve hamsi, tilen bazı ürünlerde de sucul kaynaklardan geçen MP izlerine sardalya gibi küçük balıklar açısından risk oluşturmaktadır rastlamak mümkündür. İnsan tüketimi için kullanılmayan su (Hantoro ve diğ., 2019). Balıklarda yapılan MP çalışmaları ürünlerinden yapılan ticari bir ürün olan balık ununda, polist- incelendiğinde, bulunan mikroplastik parçacıkları çoğunlukla ren (PS) ve polietilen tereftalat (PET) maddeleri tespit edil- mide ve sindirim sistemlerinde bulunmakta ve bunlar genel- miştir (Castelvetro ve diğ., 2020). Yapılan çalışmalarda, mik- likle temizleme sırasında atılmaktadır. İç organların temiz- roplastik içeren balık unu ile beslenen yetiştiricilik balıkla- lenmesi işlemi mikroplastiklerle teması doğrudan en aza in- rında MP geçişi olduğu gözlemlenmiştir (Hantoro ve diğ, direbilen bir yöntemdir (Hantoro ve diğ., 2019; Zhu ve diğ., 2019; Hanachi ve diğ., 2019). 2019). Mikroplastikler, sucul canlıların sindirim sistemlerinde yer değiştirerek başka organ ve dokulara geçebilmekte- Gıda güvenliği açısından diğer bir önemli konu da, gıda mad- dir (Browne ve diğ., 2008; Zeytin ve diğ., 2020). Levrek ye- delerinin işlenmesi sırasında potansiyel kaynaklarla MP ile minde bulunan MP’lerin (1-5 µm), çok düşük seviyelerde de kontamine olmasıdır. Su ürünlerinin, işleme teknolojileri, olsa, kas dokusuna geçebildiği tespit edilmiştir. Bu geçişin üründe kullanılan katkı maddeleri, işleme prosesinde kullanı- nasıl gerçekleştiği tam olarak bilinmemekle birlikte, mevcut lan yardımcı elemanlar, ambalaj veya dış etkenler kaynaklı çalışmada bağırsak yoluyla geçtiği tahmin edilmektedir (Zey- MP ile kontamine olabildiği düşünülmektedir (Şekil 1). İn- tin ve diğ., 2020). Benzer bir MP çalışmasında da (Karami ve san tüketimine sunulan balık, midye, ve deniz algi (nori) gibi diğ., 2017), solungaç-iç organlarda ve solungaç-iç organları canlılarda ve birçok farklı işlenmiş su ürününde MP varlığına çıkarılmış bütün (tuzlanmış-kurutulmuş) balıkta yapılan in- ilişkin çok sayıda kaynak bulunmaktadır (Van Cauwen- celemeler sonucu temizlenmiş balık etinde, iç organ içeriğin- berghe ve Janssen, 2014; Rochman ve diğ., 2015; Karami ve den çok daha fazla sayıda MP tespit edilmiştir. Bulunan bu diğ., 2017; Karami ve diğ., 2018; Zhu ve diğ., 2019; Akhba- plastik partiküllerinin sindirim sisteminden ete geçtiği düşü- rizadeh ve diğ., 2020; Gündoğdu ve diğ., 2020; Li ve diğ., nülmektedir (Karami ve diğ., 2017). Bu nedenle, gıda güven- 2020). liği açısından ileride yapılacak olan çalışmalarda MP’lerin canlı vücudu içerisindeki yerinin (translokasyonunun) ve ye- Gıda maddelerine, işleme sırasında kullanılan katkı malze- nilebilir dokuya geçişinin incelenmesi önem arz etmektedir meleri kaynaklı MP bulaşması gerçekleşebilmektedir (Lie- (Zeytin ve diğ., 2020). bezeit ve Liebezeit, 2014; Smith ve diğ., 2018). İşleme sıra- sında kullanılan su (Koelmans ve diğ., 2019), tuz (Gündoğdu, 2018), bal ve şeker (Liebezeit ve Liebezeit, 2013) gibi bazı

Aquat Res 4(1), 73-87 (2021) • https://doi.org/10.3153/AR21007 Review Article

gıda maddelerinde MNP kirliliğine rastlanmıştır. Piyasadaki sert ve diğer esnek biçimlerde ince ambalajlar şeklinde yay- balık (sardalya ve çaça balığı) konservelerinde yapılan araş- gın olarak kullanılmaktadır (Alasalvar ve diğ., 2010). tırmada 13 ülkeden alınan 20 farklı markada, düşük seviyelerde de olsa, MP izine rastlanmıştır (Karami ve diğ., 2017). Su ürünlerinin paketlemesinde yardımcı, yaygın olarak kulla- Bir diğer çalışmada da incelenen 7 farklı marka balık (ton ve nılan plastiklerden bazıları, polipropilen (PP), polistren (PS), uskumru) konservelerinin %80’inde en az 1 adet MP bulun- düşük yoğunluklu polietilen (LDPE), yüksek yoğunluklu po- muştur. Konserve balıklarda, balıkların temizlenmesi ve/veya lietilen (HDPE), lineer alçak yoğunluk polietilen (LLDPE), konservelenmesi aşamasında kullanılan katkı maddeleri po- yüksek moleküler yüksek yoğunluklu polietilen (HM- tansiyel MP kaynakları olarak bildirilmiştir (Akhbarizadeh HDPE), polyester, naylon, etilen akrilik asit (EAA) ve poli- ve diğ., 2020). Ülkemizde 5 farklı şehirde 40 farklı satıcıda akrilonitril (PAN) şeklinde sıralanabilmektedir (Alasalvar ve tüketime sunulan midye dolmalardaki (n=317) MP seviyele- diğ., 2010). rini inceleyen Gündoğdu ve diğ. (2020), toplamda 204 adet Gıdaya bulaşan MP’lerin kaynağı olarak görülen diğer risk partikül tespit edilmiştir. Paketlenmemiş olan bu midye dol- etkenleri ise ortamdaki hava ve çalışanlardır (Şekil 1). MP’le- malarda bulunan MP’lerin, işleme sırasında dış kaynaklardan rin atmosferik emisyon ile iç ve dış ortamlardaki havada bu- dolayı mı bulaştığı yoksa canlının içerisinde var olan miktar lunabildiği tespit edilmiştir (Dris ve diğ., 2017). İşleme tesis- mı olduğu bilinmemektedir (Gündoğdu ve diğ., 2020). Ben- lerinde yer alan havalandırma sistemleri ve filtreler bu açıdan zeri işlenmiş su ürünleri için bu durum tüketici sağlığı açısın- birer kontaminasyon kaynağı olup, bunları kontrolü sağlan- dan risk oluşturmaktadır. Mikroplastik konsantrasyonu en malıdır. Bunun yanı sıra çalışanların üzerinde giydiği kıya- aza indirmek için tuzlama, kurutma, dumanlama, paketleme fetlerde (önlük, bone, yüz maskesi) MP fiberler içerebilmek- vb. işleme teknolojileri sırasında oluşabilecek MP kontami- tedir ve yapılan çalışmalarda ortamdaki havada bulunan nasyon kaynakları (Şekil 1) ivedilikle incelenmelidir. MP’lerin kaynağı oldukları tespit edilmiştir (Dris ve diğ., Çapraz kontaminasyonu önlemek amacıyla kolay temizlene- 2017; Du ve diğ., 2020; Fadare ve Okoffo, 2020). İşlenmiş su bilen ve maliyeti az olan plastik malzemeler işletmelerde ter- ürünlerinde ve işleme tesislerinde yapılacak olan inceleme ve cih edilmektedir. Bununla birlikte bazı işlemede yardımcı araştırmalar sonucu bu MP’lerin kökeni ve bulaşma kaynak- makinalar ve ekipmanlar da içerisinde plastik parçalar bulun- ları incelenerek gıda güvenliği ile ilgili uygun yönergeler ve durabilmektedirler. İşleme akışındaki bu kaynaklardan gıda- limitler belirlenmelidir. lara plastik ve MP girişi olabilir (Şekil 1). Bu kaynaklardan Mikroplastikler ve İnsan Sağlığına Etkileri bazıları; plastik kesme tahtaları, bıçaklar, straforlar, işleme makinaları, çalışanların giydiği eldiven, önlükler, yüz maske- Genel olarak 150 µm veya daha büyük plastik partiküllerin leri vb. şeklinde sıralanabilmektedir. İşlenmiş ürün içerisinde bağırsak sistemi tarafından emilemediği bildirilmiştir. Yeni- bulunan plastik vb. yabancı maddeler sonucu gıda ürünleri ile lebilir kas dokusunda ve farklı organlarda bulunan MP’lerin ilgili büyük ürün geri çağırmaları meydana gelmektedir ise mideye alınan <20 µm MP’ler olduğu varsayılmaktadır (Wallace ve diğ., 2010; Fadare ve diğ., 2020; Fadare ve (EFSA, 2016; Lusher ve diğ., 2017). 0,1–10 μm aralığındaki Okoffo, 2020). Hem ekonomik açıdan hem de insan sağlığı MP'lerin ise organlara, hücre zarlarına, kan-beyin bariyerle- açısından plastik maddelerin kontaminasyonunun önlenmesi rine ve plasentaya nüfuz edebildiği belirlenmiştir (Browne ve önemlidir. diğ, 2008; EFSA, 2016; Lusher ve diğ., 2017). Benzer olarak Zeytin ve diğ. (2020), levrek balığında bulunan MP’lerin (1- İşlenmiş su ürünlerinin paketlenmesinde farklı yapıda amba- 5 μm) bağırsak sisteminden kan hücreleri yardımıyla kas do- laj malzemeleri kullanılmaktadır. Sektörde bu amaçla en çok kusuna geçtiğini varsaymaktadır. İnsanlar tarafından yutulan kullanılan materyal plastik olup, ambalaj içerisinde yer alan mikro ve nanoplastiklerin %90'ından fazlasının insan vücu- kalıntı monomerlerinin ve katkı maddelerinin son ürüne taşı- dunun boşaltım sistemi yoluyla atıldığı düşünülmektedir narak paketlenmiş ürünün kalitesini bozabildiği bilinmekte- (Smith ve diğ., 2018). İnsan hücreleri ile yapılan in vitro ça- dir. Ambalaj malzemelerinden ve bileşenlerinden onlarla te- lışma sonuçlarına göre, MP (10 μm) ve NPlerin (40-250 nm) mas eden gıda maddelerine geçen tehlikeli maddeler tüketici- insan hücreleri üzerindeki potansiyel sitotoksik etkileri gös- nin sağlığını ve güvenliğini etkilemektedir (Şekil 1) (Alasal- terilmiştir (Schirinzi ve diğ., 2017). var ve diğ., 2010; Du ve diğ., 2020; Fadare ve diğ., 2020). Önceleri cam kaplarda ambalajlı olarak sunulan birçok gıda Bununla birlikte mikro ve nanoplastikler, yapılarındaki pato- ürünü günümüzde artık plastik kaplarda paketlenmektedir jenik ve patojenik olmayan bakteriler, kimyasallar ve katkı (Wallace ve diğ., 2010). Su ürünleri işleme endüstrisinde, maddeleri kaynaklı da insan sağlığı açısından tehlike yarat- plastik ve plastik kaynaklı malzemeler, fabrikalarda ham- maktadırlar (Smith ve diğ., 2018; Dehaut ve diğ., 2019). Ya- maddelerin ve işlenmiş ürünlerin depolanmasında veya yarı

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pılan çalışmalarda sahillerde örneklenen plastiklerde polik- Kimyasal ayırma işleminde yaygın olarak asitler (HNO3, HCl lorlu bifeniller gibi kalıcı organik kirleticiler tespit edilmiştir. vb.), bazlar (KOH, NaOH vb.), okside edici ürünler (H2O2, Polisiklik aromatik hidrokarbonlar, bisfenol-A, ftalatlar gibi NaClO, Fenton ayıracı vb.) ve enzimler (Tripsin, Proteinaz K katkı maddelerinin salınımı insan vücudunda meydana gele- vb.) kullanılmaktadır (Dehaut ve diğ., 2019; Nguyen ve diğ., bilmektedir (Rochman, 2015; Akhbarizadeh ve diğ., 2020). 2019). Biyolojik matrislerin yok edilmesinde asitler oldukça Birden fazla MP kaynağına uzun süreli maruz kalındığında faydalıdır; fakat sıcaklığa göre farklılaşmakla birlikte çok vücuttaki kümülatif etki sağlık sorunlarına neden olabildiği güçlü asit veya alkali ortamlar, plastik polimerlerinin bozul- görüşü bulunmaktadır (Karami ve diğ., 2018). masına neden olup çalışmalarda analitik hatalara neden olabilmektedir (Barbosa ve diğ., 2020). Kimyasal ayırma işle- İnsan vücudundaki MP’lerin dokuda tutulma ve doku dışına minde kullanılan maddeler, plastiğe etkisi ve analiz açısından atılım oranı, şekil, boyut, polimer tipi, yüzey kimyası ve içer- etkinliği hakkında literatürde metodoloji çalışmaları da yapıl- dikleri kimyasal maddeler gibi çeşitli faktörlerden etkilen- maktadır (Dehaut ve diğ., 2016; Karami ve diğ., 2017). mektedir (Smith ve diğ, 2018). MP’lerin hem insanlar hem de su ürünleri üzerindeki uzun vadeli etkileri tam olarak bilin- Plastikler, bulundukları ıslak çevresel ortamdan daha az yo- memektedir. MP’lerin insan sağlığı üzerine etkileri, tüketilen ğun ve daha hidrofobik olma eğiliminde olduklarından dolayı konsantrasyon seviyesine bağlıdır ve günümüzde MP tüketim yoğunluk farkı ile de yüzdürülerek kolayca ayrılıp ardından miktarına ilişkin yasal sınır değerler henüz düzenlenmemiştir boyut ayırma yoluyla filtrelenirler (Silva ve diğ., 2018; (Smith ve diğ., 2018; Zeytin ve diğ., 2020). Yapılan çalışma Nguyen ve diğ., 2019). MNP'lerin ayrılması için yoğunluğa sonuçlarından midye tüketim oranı ve maruz kalınan MP sa- dayalı ayırmada NaCl, NaI, KI, ZnCl2, ZnBr2 gibi doymuş tuz yısı hesaplandığında, Avrupa’nın yüksek miktarda midye tü- çözeltileri kullanılmaktadır (Barbosa ve diğ., 2020). Plastik keticilerinin kişi başı yılda 11.000 adete kadar MP yuttuğu polimerlerin yoğunluğu 0,8-1,7 g cm-3 arasında değişmekte- sonucuna varılmıştır (Van Cauwenberghe ve Janssen, 2014). dir (Löder ve Gerdts, 2015). İnsanların gıda yoluyla maruz kalabileceği gerçek mikroplastik miktarını değerlendirmek için yeterli bilgi bulunmamak- Literatürde önerildiği üzere, yoğunluk ayrımları rutin olarak tadır ve bu konuda yapılacak olan araştırmalara ihtiyaç du- santrifüjleme yoluyla gerçekleştirilmektedir (Nguyen ve diğ., yulmaktadır. 2019). MP’lerin yoğunluk farkı veya santrifüj yoluyla balık dokusundan ayrımı başarılı olarak literatürde uygulanmıştır Mikroplastiklerin ve Nanoplastiklerin (Karami ve diğ., 2017; Gündoğdu ve diğ., 2020). İdentifikasyonu ve Sayımı Ayrıca bulundukları ortamın katı içeriği düşük olduğunda, Mikroplastikleri ve Nanoplastikleri Ortamdan Ayırma plastikler boyut bazlı filtreleme ile kolayca ayırt edilebilirler Teknikleri (Nguyen ve diğ., 2019). Bu yöntemlerin dezavantajı küçük boyutlu partiküller için dışarıdan da kontaminasyon olabile- Mikro ve nanoplastiklerin (MNP) doğru ve kolay tanımlan- ceği için riskli olmasıdır. ması için analizi yapılacak karmaşık yapılı örneklerden plastik partiküllerini izole etmek gerekmektedir (Nguyen ve diğ., Fiziksel ayırma işleminde ise filtrasyon, ultrasonik ve yerçe- 2019). Bu partikülleri izole etme teknikleri; elle manuel ola- kimi kaynaklı ayırma teknikleri kullanılmaktadır. Filtrasyon rak ayırma veya partiküllerin fiziksel ve kimyasal özellikle- işleminde filtre tıkanmadan olabildiğince küçük partikülleri rinden yararlanılarak ayırma şeklinde uygulanmaktadır. Di- yakalayıp ayırması temel alınmalıdır. Çalışmalarda giderek seksiyon, fiksasyon ve kriyoseksiyon yöntemleri manuel ola- daha küçük gözenek boyutlarının kullanıldığı sıralı filtre- rak partiküllerin ayrımında kullanılan ucuz yöntemlerdir (De- leme, filtre tıkanmasını en aza indirebilen bir yöntem olarak haut ve diğ., 2016; Nguyen ve diğ., 2019). Diseksiyon işlemi, uygulanabilir (Dehaut ve diğ., 2016; Nguyen ve diğ., 2019). balık, balina, midye vb. canlıların gastrointestinal sistemle- Filtrelemeden sonra, örneklerdeki partiküllerin kalitatif rinde >500 μm mikroplastiklerin görsel olarak tanımlanması (renk, şekil ve bileşen tanımlama) analiz ve niceliksel analiz için kullanılan bir yöntemdir. Bununla birlikte, daha küçük (sayısı ve boyut dağılımı/aralığı) için filtrede tutulması gerek- mikroplastikler diğer dokulara ve organlarda yer değiştirebil- mektedir (Hidalgo-Ruz ve diğ, 2012). mektedir ve fiksasyon ve kriyoseksiyon yöntemleri ise bu tip Doğru Filtre Seçiminin Önemi örneklerde, farklı MP translokasyonlarını (Karaciğer dokusu gibi) incelemede yararlı olabilmektedir (Nguyen ve diğ., Kullanılan filtrenin gözenek boyutu ve türü yapılan çalışma- 2019). Bu yöntemler karmaşık biyolojik materyallerde yeter- ların hassasiyeti açısından oldukça önemlidir (Dehaut ve diğ., siz olabilmektedirler. 2019; Toussaint ve diğ., 2019; Cai ve diğ., 2020). Filtrelerin yapı tipleri ve gözenek boyutları MP’lerin miktar tayini üze-

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rinde etkili olup yanlış filtre kullanımı örnekteki MP sayısı- Standartlaştırılmış bir MP analizi gerçekleştirmek için bu nın eksik hesaplanarak yanlış sonuca neden olabilmektedir. adımlar önemlidir. Gözenek boyutu azaldıkça bulunan plastik parçaların sayısı da artmaktadır (Toussaint ve diğ, 2019; Cai ve diğ, 2020; Mikroplastikler her alanda bulunduğu için analizden önce ve Akhbarizadeh ve diğ., 2020). analiz sırasında numune kontaminasyonu kaçınılmazdır (Bar- bosa ve diğ., 2019). Çalışmalarda kontaminasyon seviyesi MP çalışmalarında, örnekleme yöntemini ve özellikle kulla- kontrol yapılarak sürekli her aşamada belirlenmelidir. Bunun nılacak ağ/membran filtre türlerini açıklayan tek tip bir pro- için ortama temiz bir cam petride filtre kâğıdı bırakılır ve her- tokol henüz bulunmamaktadır. Su numunelerinde MP analizi hangi bir aşamada MP kontaminasyonu gerçekleştiğinde sa- yapılan bazı araştırmalarda, örnekler Manta-trol ve nöston yısı belirlenir (Dehaut ve diğ., 2019). vb. ağlarla toplu olarak filtrelenmektedir (GESAMP, 2015). Örneklemeden sonra, MP’leri ayırmak için naylon, nitroselü- Mikroplastiklerin ve Nanoplastiklerin loz, cam elyaf, polikarbonat veya paslanmaz çelikten yapıl- Kompozisyonlarının Tespitinde, mış çeşitli filtreler kullanılmaktadır (Cincinelli ve diğ., 2017; Tanımlanmasında ve Miktarlarının Güven ve diğ., 2017; Dehaut ve diğ., 2019; Toussaint ve diğ., Belirlenmesinde Kullanılan Teknikler 2019; Cai ve diğ., 2020). Mikro ve nanoplastiklerin karakterizasyon yöntemlerinde Partiküllerin tutulma şekillerine bağlı olarak membran filtre- kullanılan cihaz ve metotların avantaj ve dezavantajları ler, gözenek derinliği ve gözenek genişliğine göre iki tipte sı- Tablo 1’de özetlenmiştir. nıflandırılır. Gözenek derinliğine sahip filtreler, paslanmaz çelik ağ, naylon, cam elyaf/pamuk elyaf ve nitroselüloz/karı- Görsel Analiz Metotları şık selüloz filtrelerdir. Yapı olarak birbirinden farklı olan bu Yapılan çalışmalarda; parçacığın boyutlarının ve morfolojisi- filtre türlerinin gözenekleri derin ve kıvrımlı olup boyutları nin belirlenmesi ve polimer miktarının belirlenip ve ölçül- ortalama bir değerdir (Yu ve diğ., 2010). Polikarbonat memb- mesi elzemdir. Beş yüz µm’ye kadar olan partiküllerin görsel ran filtreler gibi gözenek genişliğine göre sınıflandırılan filt- gözlemi basit olarak, çıplak gözle veya bir diseksiyon mik- relerde ise ölçülen dairesel gözenekler filtrenin gerçek boyutu roskobu kullanılarak yapılabilmektedir (Renner ve diğ., olup, kanalları ise sığ ve düzdür (Cai ve diğ., 2020). 2018). Daha ayrıntılı incelemeler için farklı cihazlar kullanıl- Çalışmalarda seçilen filtre ve etkinliğini inceleyen Cai ve diğ. maktadır. Partiküllerin boyut ve morfolojik açıdan ayrımında (2020), filtre türü ve gözenek boyutunun yapılacak olacak ça- optik, elektron ve tarama özelliklerine dayanan polarize ışık lışma koşullarına uygun olarak minumum zaman alacak şe- mikroskobu, stereoskop veya floresan mikroskobu kullanıl- kilde seçilmesi gerektiğini önermiştir. Filtrenin seçilen göze- maktadır (Barbosa ve diğ., 2020). Bu yöntemler hızlı, ucuz nek boyutu, MP analizinin daha sonraki aşaması olan mikros- ve kolay metotlar olmasına rağmen plastik polimerlerinin kopla gözlem, seçim ve tanımlama aşamalarıyla da tutarlı ol- kimyasal yapılarını tanımlamada sınırlı potansiyele sahiptir- malıdır. ler ve insan hatasına da oldukça açık metotlardır (Silva ve diğ., 2018). Taramalı Elektron Mikroskobu (SEM), Trans- Laboratuvar Ortamında Mikroplastik misyon Elektron Mikroskobu (TEM), Taramalı Tünelleme Kontaminasyonunun Kontrolü Mikroskobu (STM) gibi elektron ve taramalı prob mikros- Mikroplastiklerin analizinin yapıldığı ortam ve kişilerden kopları, MP’lerin ayrımını görüntü tabanlı tekniklerle incele- kaynaklı bulaşma söz konusu olup bu durum analiz sonuçla- yen yaygın tekniklerdir; fakat aynı zamanda büyük ölçekli rının olduğundan fazla hesaplanmasına neden olabilmektedir analizlerde oldukça zaman almaktadırlar (Nguyen ve diğ., (Dehaut ve diğ., 2019). Laboratuvar ortamında çalışan kişile- 2019). rin pamuk yerine sentetik yapılı kumaşlardan yapılma önlük kullanımı sonucu MP bulaşması söz konusu olabilmektedir (Van Cauwenberghe ve diğ, 2013; Dehaut ve diğ., 2019). Bu- nun yanı sıra çalışanların ellerinde de tekstil kaynaklı MP fiberleri bulunabilir. Bunun önlenmesi adına filtrelenmiş su/al- kol solüsyonları veya basınçlı hava kullanılması önerilmek- tedir. Analiz yapılan alan temiz filtreye sahip olduğundan emin olunan laminer hava akışlı tezgah veya davlumbaz ol- malıdır. Kullanılan çözeltilerin hepsi önceden düşük mikron boyutlarında filtreden geçirilmelidir (Dehaut ve diğ., 2019).

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Tablo 1. Mikro ve nanoplastiklerin karakterizasyon yöntemlerinin avantaj ve dezavantajları (Shim ve diğ., 2017; Silva ve diğ., 2018; Nguyen ve diğ., 2019 ve Toussaint ve diğ., 2019’ dan modifiye) Table 1. Advantages and disadvantages of characterization methods of microplastics and nanoplastics (Modified from Shim et al., 2017; Silva et al., 2018; Nguyen et al., 2019 and Toussaint et al., 2019) Tespit/Tanımlama/Miktar Cihaz Avantajları Dezavantajları Belirleme Yöntemleri Diseksiyon Mikroskobu Kimyasal doğrulama yok; Yüksek oranda yanlış Polarize Işık Mikroskobu tanımlama olasılığı; Küçük ve şeffaf plastik Floresan Mikroskobu Basit, hızlı ve kolay analiz imkanı; Diğer metotlara partiküllerin eksik olma olasılığı yüksektir; Görsel Analiz Taramalı Elektron Mikroskobu (SEM) göre daha ucuz Polimer bileşimi tanımlanamaz; Büyük ölçekli Transmisyon Elektron Mikroskobu (TEM) analizlerde zaman alıcı Taramalı Tünelleme Mikroskobu (STM) FTIR spektroskopisi Polimeri tanımlar; Seçici ve tekrarlanabilir analiz; Polimer yapısı zarar görmüş örneklerde etkili Küçük numune miktarları gerektirir; Örneğin ön değildir; FTIR-mikroskop kombinasyonu Mikro-FTIR Spektroskopisi (µ-FTIR) işlem hazırlığı azdır; Örneği tahrip etmez; Canlı pahalıdır; Geniş alan görüntüleme için zaman alıcı organizmalardaki kalıntıları lokalize edebilir (20 saate kadar süren) Azaltılmış Toplam Yansımalı-Fourier Dönüşüm Polimeri tanımlar; Örneğin ön işlem hazırlığı azdır; Büyük partikülleri tanımlayabilir; Örneği tahrip Optik Titreşim Kızılötesi Titreşimli Spektroskopisi (ATR-FTIR) Hızlı ve ucuz analiz edebilir Spektroskopisi Polimeri tanımlar; Seçici ve tekrarlanabilir analiz; Örneklerin otomatik floresansı, Raman sinyalini Küçük numune miktarları gerektirir; Örneğin ön maskeleyebilir; Polimer yapısı zarar görmüş Mikro-Raman Spektroskopisi (µ-Raman) işlem hazırlığı azdır; Kısmen tahribatsız analiz örneklerde etkili değildir; Örnekler lazerle zarar eder; Raman mikroskobu, tek tek mikron altı görebilir; Geniş alan görüntüleme için zaman alıcı parçacıkları ve türlerini tanımlayabilir; Canlı (38 saate kadar); Raman mikroskop aletleri organizmalardaki kalıntıları lokalize edebilir pahalıdır Sadece belirli polimerleri tanımlayabilir (SEM ile Polimeri tanımlar; Karbon baskın plastiklerin X-ışını Enerji Dağılımlı X-ışını Spektroskopisi kombine edildiğinde); Kombine EDS cihazları inorganik parçacıklardan ayrımında etkilidir (SEM Spektroskopisi (EDS, EDX, EDXS veya XEDS) pahalıdır; Uzun zaman ve çaba gerektiren ön işlem ile kombine edildiğinde). gerektirir Polimerleri tanımlar; Yüksek uzaysal çözünürlüklü görüntüleme mümkündür; Örneği tahrip etmez; Kompleks data içeriğinden dolayı uzman bir Parçacık karışımları için uygundur; Düşük µm operatöre ihtiyaç vardır; Pahalıdır; Hava İkincil İyon Kütle Uçuş Zamanlı İkincil İyon Kütle Spektrometresi aralığında parçacıkları tespit edebilir (ppm ile ppb koşullarına veya yüzey kirleticilerine göre Spektrometresi (TOF-SIMS) arasını dahil analiz edebilir); Potansiyel olarak tanımlamada yanlışlık olabilmektedir; Numune, inorganik ve organik kimyasal kirleticiler (ağır vakum uyumlu olmalıdır metaller) hakkında bilgi sağlayabilir Hızlı, basit; Referans malzemeleri kullanarak Diferansiyel Tarama Kalorimetre (DSC) Polimer karışımlarına sınırlı uygulama polimerleri tanımlar Polimerleri ve organik katkı maddelerini tanımlar; Zaman alıcı; Örneği tahrip eder; Partikül Kütle konsantrasyonundaki küçük miktarları numarası, boyutu ve şekli hakkında sonuç vermez; Piroliz-Gaz Kromatografisi-Kütle Spektrometrisi belirler (<0.5 mg); Örneğin ön işlem hazırlığı Kompleks data içeriğinden dolayı uzman bir (Pyr-GC/MS) azdır; Biyolojik matrisler ve çevresel örnek operatöre ihtiyaç vardır; Daha düşük partikül Termal Analizler taraması için uygundur boyutunu mm' nin kesirleri ile sınırlayan numunenin manuel manipülasyonu gerekli Polimerleri ve organik katkı maddelerini tanımlar; Örneği tahrip eder; Zaman alıcı; Kalitatif Termal Ekstraksiyon ve Desorpsiyon-Gaz Örnek hazırlama aşaması kolaydır, Örneğin ön analizlerde sınırlı ölçüm Kromatografisi/Kütle Spektrometrisi (TDS-GC-MS) işlem hazırlığı azdır; Yüksek kütleli (100 mg’ a

kadar) örneklerdeki miktarları belirler

Aquat Res 4(1), 73-87 (2021) • https://doi.org/10.3153/AR21007 Review Article

Optik Titreşimli Spektroskopi ve diğ., 2017; Silva ve diğ., 2018). Buna ek olarak, bir diğer benzer yöntem olan Uçuş Zamanlı İkincil İyon Kütle Spekt- MP polimer parçacıklarını tanımlama ve sayımını aynı anda rometresi (TOF-SIMS) cihazı ile de, SEM-EDS cihazı ile yapabilen Raman ve Fourier Dönüşüm Kızılötesi (FT-IR) tit- analizi mümkün olmayacak bazı organik malzemelerden ve reşimli spektroskopileri de kullanılmaktadır. Bu spektrosko- doku bölümlerinden polietilen gibi MP’lerin karakterizas- pik yöntemler örneği tahrip etmeden analiz etmeyi sağlayan yonu yapılabilmektedir (Jungnickel ve diğ., 2016; Toussaint nispeten yavaş, fakat kesin ve doğru sonuç veren tekniklerdir. ve diğ., 2019). FTIR mikroskopları 5 μm'ye, Raman ise 1 μm'ye kadar açısal (uzaysal) çözünürlüğe sahiptirler (Elert ve diğ., 2017; Termal Analiz Metotları Nguyen ve diğ., 2019). Genellikle, daha büyük MP'ler ATR- FTIR (Azaltılmış Toplam Yansımalı-Fourier Dönüşüm Kızı- Termal analiz, belirli polimer türlerinin kimyasal tanımlan- lötesi Titreşimli Spektroskopisi) ile tanımlanırken, 20 µm'ye ması için spektroskopiye dayalı yöntemlere alternatiftir. Bu kadar olan MP’ler µ-FTIR ile ve ≤20 µm olan MP’ler ise µ- yöntemlerin en önemli dezavantajı, cihaza verildikten sonra Raman ile karakterize edilir (Käppler ve diğ., 2016; Veerasin- MP numunelerini tahrip ederek analiz etmeleridir (Shim ve gam ve diğ., 2020). İki yüz–300 µm'den büyük boyutlu tek diğ., 2017). partiküller ise, FTIR analizinden önce görsel inceleme yapı- Diferansiyel tarama kalorimetrisi (DSC), polimerik malze- larak analiz edilmektedir. ATR-FTIR analizi maliyet etkin bir melerin termal özelliklerini incelemek için yararlı bir yön- yöntem olduğundan ve örnek hazırlama veya karmaşık mate- temdir. Yöntem, polimer türlerini tanımlamak için referans matiksel işlem gerektirmediğinden ötürü olmadığından tercih malzemeleri gerektirir, çünkü her plastik ürün, DSC'de farklı edilmektedir; fakat analiz sonucunda MP örneği kristal ile özelliklere sahiptir. DSC ile analiz nispeten basit ve hızlıdır; ezildiğinden ötürü tahrip görebilmektedir (Veerasingam ve ancak çevresel numunelerde karışık polimer ürünlerden diğ., 2020). µ-FTIR ise, dedektör yardımıyla daha geniş filtre MP’lerin tanımlanmasında sınırlıdır (Shim ve diğ., 2017; To- alanlarının yüksek çözünürlüklü kimyasal görüntülemesine ussaint ve diğ ., 2019). izin veren bir cihazdır (Cincinelli ve diğ., 2017). µ-FTIR ve Raman spektroskopisini karşılaştıran Käppler ve diğ. (2016), Bununla birlikte plastik partiküllerin kimyasal bileşimleri özellikle ≤20 µm parçacıklar için daha hassas ölçüm yapabi- (polimer türü) ise, spektroskopi veya kütle spektrometrisine len Raman spektroskopisini önermiştir; fakat bu yöntem µ- dayalı teknikler kullanılarak incelenebilmektedirler. Bu tek- FTIR spektroskopisine (yaklaşık 20 saate kadar) göre daha niklerden polimerlerin hızlı tanımlanmasında etkili ancak bo- çok zaman aldığı için (yaklaşık 38 saate kadar) metot terci- yut dağılımlarını belirleyemeyen Pyr-GC/MS (Piroliz-gaz hinde sıkıntı oluşturmaktadır (Tablo 1). Ayrıca Raman tekno- kromatografisi-kütle spektrometrisi) veya TDS-GC-MS lojisinin diğer dezavantajları arasında, fiberleri veya pigment (Termal Ekstraksiyon ve Desorpsiyon-Gaz Kromatogra- içeren parçacıkları kolayca tanımlayamaması ve lazerinin fisi/Kütle Spektrometrisi) gibi örnek tahrip edici termoanali- yüksek enerji yoğunluğu nedeniyle plastik numune parçacık- tik yöntemler en yaygınlarıdır (Zeytin ve diğ., 2020). larını tahrip etme özelliği bulunmaktadır (Dehaut ve diğ., Pyr-GC/MS yüksek sıcaklıklarda ayrıştırılan numunelerin 2019). FTIR cihazının ise, nem içeriğine karşı duyarlı olması gaz kromatografisi ile ayrılması ve kütle spektrometrisi ile ve siyah partikülleri tanımlamadaki yetersizliği dezavantaj- analizini içeren bir cihazdır (Nguyen ve diğ., 2019). Piroliz ları arasında sıralanabilir (Käppler ve diğ., 2016). Yapılan ça- gaz kromatografisi-kütle spektrometrisi tekniğinin avantajı, lışmalardan özetle, FTIR Raman’a göre küçük partikülleri katı numune doğrudan cihaza verilebildiği için ön işlem ihti- (özellikle <20 µm, analiz etmede daha yetersiz olduğundan yacını ortadan kalkmış olur ve örnek miktarı oldukça azdır %35 daha az plastik tespit edebilmektedir (Käppler ve diğ., (5-200 µg). Sadece numune başına polimer kütlesini ölçen 2016). Pyr-GC-MS'nin mikroplastiklerin sayısını, türünü veya mor- FTIR ve Raman cihazlarına ek olarak, SEM, TEM vb. elek- folojisini belirlemede yararlı değildir, bu nedenle MP’lerin tron mikroskobu ile görüntülenen MP’ler, Enerji dağılımlı X- analizinde optik tekniklerle birlikte kullanılmalıdır (Dehaut ışını spektroskopisi (EDS) ile analiz edilerek temel bileşim- ve diğ., 2016; Silva ve diğ., 2018). leri identifiye edilebilmektedir. Kombine SEM-EDS cihazı TDS-GC-MS, numunenin 1000°C'ye kadar olan sıcaklıklara maliyet açısından pahalıdır ve örnek hazırlama ve örnek in- ısıtılmasıyla kütlesinin termogravimetrik olarak ölçülmesi celeme için önemli ölçüde zaman ve çaba gerektirir, bu da prensibine dayanır (Nguyen ve diğ., 2019). Nispeten yüksek analiz edilebilecek örnek sayısını sınırlamaktadır. MP’lerin kütleli (100 mg'a kadar) numuneler için uygun bir tekniktir; renkleri SEM cihazında tanımlayıcı olarak kullanılamaz, bu ancak kalitatif analizlerde sınırlıdır (Duemichen ve diğ., nedenle bu cihaz sadece plastik parçacıkların yüzey karakte- 2015; Nguyen ve diğ., 2019). TDS-GC/MS ile karşılaştırıldı- rizasyonu ve temel bileşim analizi için önerilmektedir (Shim

Aquat Res 4(1), 73-87 (2021) • https://doi.org/10.3153/AR21007 Review Article

ğında, Pyr-GC/MS yaklaşık 50 μg' a kadar olan nanoplastik- Sea: Background levels and selective contamination of plank- lerin tanımı ve ölçümünde daha hassastır (Nguyen ve diğ., tivorous diving seabirds. Environmental Pollution, 219, 2019). 1131-1139. https://doi.org/10.1016/j.envpol.2016.09.017 Sonuç Günümüzde oldukça popüler bir çalışma alanı haline gelen su Andrady, A. L., Neal, M. A. (2009). Applications and soci- etal benefits of plastics. Philosophical Transactions of the ürünlerinde mikroplastik kirliliği insan sağlığı açısından araş- Royal Society B: Biological Sciences, 364(1526), 1977-1984. tırılması gereken önemli bir konudur. İnsanların su ürünleri https://doi.org/10.1098/rstb.2008.0304 kaynaklı mikroplastik tükettiği bilinmektedir. Bu tüketim hesaplanarak, insanlar için günlük limit alım değerlerinin belir- Andrady, A.L., Rajapakse, N. (2019). Additives and Che- lenmesi elzemdir. İnsan tüketimine sunulan işlenmiş su ürün- micals in Plastics. In Handbook of Environmental Che- lerinde bulunan MP’lerin, sucul kirlilik kaynaklı mı yoksa iş- mistry (Vol. 78, pp. 1-17). Springer Verlag. ISBN: 978-3- leme prosesleri sırasında mı bulaştığıyla ilgili kaynağı tespit 319-95566-7 https://doi.org/10.1007/698_2016_124 etmeye yönelik henüz bir çalışma bulunmamaktadır. Gıda gü- venliği açısından MP’lerin analizi, insan sağlığı açısından Ašmonaitė, G. (2019). Microplastics in the aquatic environ- riskleri ve tüketilen gıdalara MP’lerin bulaşma kaynakları ment: Insights into biological fate and effects in fish. (Docto- ral Dissertation) University of Gothenburg. Faculty of Sci- gibi çalışma konularının uygun metot ve araştırma yöntemleri ence, Department of Biological and Environmental Sciences, kullanılarak araştırılması gerekmektedir. Gothenburg, Sweden.

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87 AQUATIC RESEARCH E-ISSN 2618-6365

Aquat Res 4(1), 88-115 (2021) • https://doi.org/10.3153/AR21008 Review Article

Checklist of marine diatoms from the Turkish coastal waters with updated nomenclature

Aydın KALELİ , Reyhan AKÇAALAN

Cite this article as: Kaleli, A. Akçaalan, R. (2021). Checklist of marine diatoms from Turkish coastal waters with updated nomenclature. Aquatic Research, 4(1), 88-115. https://doi.org/10.3153/AR21008

Istanbul University, Faculty of Aquatic ABSTRACT Sciences, Department of Marine and Freshwater Resources Management, Marine diatom research in the coastal waters of Turkey started nearly two centuries ago. In the last Istanbul, Turkey decades, increasing numbers of contributions extended the knowledge of the marine phytoplankton. While several studies dedicated to planktonic forms and the checklists published concerning on the phytoplankton, relatively low numbers of benthic diatom studies were performed. There- fore, this is the first detailed list of the marine diatoms including both planktonic and benthic forms in Turkish coasts. This paper brings up the checklist of the past research referring to the authors in ORCID IDs of the author(s): the last two centuries within the scope of the latest nomenclature. A total of 767 taxa (species, A.K.. 0000-0003-3843-1335 varieties and forms) belonging to 183 genera were listed. This study focussed into the study areas R.A. 0000-0002-0756-8972 according to the reviewed literature and showed that many areas are yet to be investigated. Keywords: Biogeography, Checklist, Epilithic, Epipelic, Epiphytic, Marine diatoms, Phytoplankton, Turkey

Submitted: 08.10.2020 Revision requested 21.12.2020 Last revision received 23.12.2020 Accepted: 23.12.2020 Published online: 25.12.2020

Correspondence: Aydın KALELİ E-mail: [email protected]

Available online at

http://aquatres.scientificwebjournals.com

Aquat Res 4(1), 88-115 (2021) • https://doi.org/10.3153/AR21008 Review Article

Introduction The knowledge of biodiversity and biogeography of diatoms the Sea of Marmara, and Taş and Okuş (2016) from the Black showed remarkable progress in the last two centuries. In ma- Sea. A checklist of freshwater algae, which includes freshwa- rine diatoms, drawings contributed into systematics and bio- ter diatoms, by Aysel (2005), also covered many benthic dia- geography of the diatoms in mid-late 19th century and con- toms; however, any lists comprising exclusively marine ben- tinued within the early 20th century with many atlas and mon- thic diatoms has yet not published. Even though research on ographs (Smith, 1853; Schmidt, 1874-1959; Cleve, 1894- marine phytobenthos is increasing, the biodiversity in the ma- 1895; Peragallo and Peragallo, 1897-1908), which are still rine coasts and the biogeography of the diatoms in Turkey fundamental sources for marine diatom researchers. In the remained unclear. The low number of studies conducted in last decades with the aid of light microscopy (LM) and scan- the coastlines and the outdated nomenclature used in the pre- ning electron microscopy (SEM), many species were discov- vious papers prevented to produce a collective list of the ben- ered in the marine coastal waters, which extended the thic diatoms, even though, Turkey surrounded by seas; Black knowledge of diatom assemblages from different coasts. The Sea, Mediterranean Sea, the Aegean Sea, and has an inland recent monographs revealed many endemic species and in- sea; the Sea of Marmara. However, several benthic studies creased the data of widespread taxa and some location-spe- were already performed, or checklists were published in the cific taxa with introductions to new locations; e.g., Baltic Sea, adjacent countries, e.g., Romania (Caraus, 2002, 2012, 2017); Snoeijs (1993), Snoeijs and Vilbaste (1994), Snoeijs and Russia (Nevrova, 2016); Greece (Foged, 1986; Louvrou, Potapova (1995), Snoeijs and Kasperovičienè (1996), and 2007). Snoeijs and Balashova (1988), the Bahamas Hein et al. (2008), the Mediterranean, Blanco and Blanco (2014), Mad- Furthermore, the lack of drawings and micrographs or mor- agascar Metzeltin and Lange-Bertalot (2002), Kryk et al., phological features allowed most of the taxa remained as (2020), the Pacific, Lobban et al., (2012), Stidolph et al., doubtful in the past studies (Koray 2001). There were re- (2012). Witkowski et al. (2000) published a monograph of the cently increasing research, including morphological details taxa from different locations of the marine coasts around the providing comparable data for further studies. However, world. These monographs and checklists (Hendey, 1974; there was still a need for marine diatom lists to understand López-Fuerte and Siqueiros-Beltrones, 2016) provided com- and enhance taxonomy and biogeography of diatoms in Turk- plete biogeographical dispersal of the benthic diatoms and led ish coasts. further studies in family, genus or even taxon-specific levels This paper aimed to create a list of reported marine diatom (molecular and phylogeny). species with updated nomenclature in the coasts of Turkey The first study in Turkish coastal waters conducted in mid with an emphasis on doubtful and illustrated taxa within the 19th century; Ehrenberg (1844), described species from the results of major marine diatom studies performed so far. The Bosphorus in the Sea of Marmara, after some time, Hustedt list was created to gather all the scattered previous data to also described species with drawings in Bosphorus and the provide a comparable key particularly relying on the illus- Golden Horn in the Sea of Marmara (Hustedt, 1930-1966). trated taxa for the future research in Turkey. Simonsen (1987) illustrated these taxa from Hustedt collec- Methodology tion later. However, the first studies were conducted quite a while ago in Turkey; still today, there is very little data in This diatom checklist was created using information from the terms of benthic diatoms. The past papers published on the publications between 1844-2020. The literature search re- phytoplankton of Turkish coastal waters included several vealed 56 references included planktonic diatoms and marine species with ≥ 30 µm diameter which also observed in the benthic diatoms in the coasts, coastal lake and lagoons of Tur- benthos. Therefore, some diatom taxa living in benthos with key. Habitat information and the study areas were presented relatively bigger cell size or showing centric morphology for each species (Table 1). The references included articles, which allow cells to suspend in the water column easily (e.g., reviews, checklists, PhD and MSc thesis. Freshwater species Pleurosigma elongatum W. Smith, Striatella unipunctata reported in some studies were not excluded due to riverine (Lyngbye) C. Agardh, Navicula directa (W. Smith) Brébis- pressure and salinity changes in different locations from the son, Coscinodiscus spp.) were reported from the surface wa- Mediterranean to the Black Sea. However, there were several ters or open waters in Turkish seas. Several authors published marine diatom species found in inland waters, according to checklists regarding phytoplankton composition in the last Maraşlıoğlu and Gönülol (2020), these taxa were not taken decades. Koray (2001) reported the phytoplankton from into account due to possible misidentifications. Turkish seas, while Balkıs (2004) published a checklist from

Aquat Res 4(1), 88-115 (2021) • https://doi.org/10.3153/AR21008 Review Article

Some species reported with different names from the latest out the years. Several checklists published in the past by var- taxonomical order. An effort was put to classify the species ious authors (Koray, 2001; Balkıs, 2004; Taş and Okuş, with the updates to their current names, according to Guiry 2016), however, the latest and progressing systematics of di- and Guiry (2020) and Kociolek et al. (2020). Systematic clas- atoms resulted in many synonyms and transferred taxa into a sification followed Round et al. (1990). Taxa cited in species- new species of a genus. This paper brings the data altogether level with “confer” and “sp.” were not evaluated in the list with the latest nomenclature with an emphasis on the current due to a need of confirmation of these species. names of the cited taxa. An essential part of the studies performed dedicated to mostly planktonic forms of diatoms; the Many species lack images and even reported for the first time, papers here reviewed generally had both benthic and plank- there were no illustrations or morphological features (e.g., di- tonic diatoms. The number of the taxa seems to be high in the mensions, striae or fibulae counts). Therefore, references checklist; however, diatom species number from the coasts of used in the list with illustrations were shown with an asterisk Turkey are yet far from similar checklists (Hendey, 1974; in Table 1. López-Fuerte and Siqueiros-Beltrones, 2016; Caraus, 2017). The Current Status of Marine Diatoms in The number of only benthic species determined in the Adri- Turkey atic Sea was 518 (Viličić et al., 2002). In Turkey, the reason for a low number of taxa might be related to the low number The list contained a total of 767 taxa (species, varieties and of benthic studies performed in these coasts. Most of the stud- forms) belonged to 183 genera. Amongst all, 70 taxa be- ies reviewed in this paper used a similar sampling technique longed to class Coscinodiscophyceae, 130 taxa to Medi- (plankton net), which aimed to take phytoplankton; and in ophyceae and 567 taxa to Bacillariophyceae (See Checklist). some of these studies, benthic diatoms were also observed. Current nomenclature of the formerly reported taxa was listed Therefore, the most cited taxa found to be relatively higher in (See Updated Nomenclature). According to the literature, the cell size, which observed through the plankton net. However, most cited genera with highest numbers of species were Na- the recent findings showed (Kaleli et al., 2020) that the num- vicula Bory (57), Nitzschia Hassal (55), Chaetoceros Ehren- ber of taxa could increase with the forthcoming studies, berg (53), Mastogloia Thwaites (31), Cocconeis Ehrenberg which especially aim to reveal benthic species. (23), Amphora Ehrenberg ex Kützing (18), Halamphora (Cleve) Mereschkowsky (16). The most common six genera The checklist revealed that a high number of freshwater taxa in terms of species numbers consisted of 33.1% of all taxa observed in these studies (Cymbella spp., Gomphonema spp., found in the literature. The most common species were Cyl- Navicula spp.) mostly in the Black Sea coasts (Soylu et al., indrotheca closterium (Ehrenberg) Reinmann & Lewin 2011; Baytut et al., 2016). It might be related to the freshwa- which was reported from 21 studies and followed by ter inputs e.g., two major rivers; Kızılırmak and Yeşilırmak, Nitzschia longissima (Brébisson ex Kützing) Grunow (cited where relatively lower salinity might be a factor to detect the 19), Coscinodiscus radiatus Ehrenberg, Thalassionema freshwater diatoms in the Black Sea and yielded favourable nitzschioides (Grunow) Mereschkowsky, Pleurosigma nor- conditions for the taxa to survive; however, it was observed manii Ralfs (cited 17), Licmophora abbreviata Agardh, that marine taxa could dominate in these coastal waters Achnanthes brevipes Agardh (cited 15) (Table 2). (Kaleli et al., 2017) as well as in the northern Black Sea coasts (Nevrova and Petrov, 2019). Many taxa reported in the list The reviewed literature revealed that studies in the coastal have no documentation or sufficient data on geographical dis- waters of Turkey were low in numbers. The Sea of Marmara tribution. It is difficult to evaluate the local distribution of the and the Aegean Sea was the most intensively studied areas species in comparison to the papers reviewed; however, the with 20 and 19 studies, respectively. Studies in the Mediter- list gives an insight into the underlying distribution in the seas ranean and the Black Sea were rather scarce with 11 and 14 of Turkey. The studies used in this checklist revealed that research in terms of both benthic and planktonic species com- many species lack morphological features and documented as position and biogeographical dispersal. the first record in Turkey. However, in newly reported taxa, LM, SEM and molecular techniques should be given in detail The current paper represents the first exclusively detailed ma- for comparison with the species found in the coasts of Tur- rine diatom list in the Turkish coastal waters. Since the stud- key, other coastal areas and beyond. Therefore, this paper re- ies started in 1844 with Ehrenberg, several authors showed a vealed the diatom composition in the Turkish coastal waters significant contribution to the diatom composition through- with the latest nomenclature and could be used as a fundamental list for the latter studies.

Aquat Res 4(1), 88-115 (2021) • https://doi.org/10.3153/AR21008 Review Article

Table 1. Literature with all species or partially reported with illustrations marked with an asterisk. Black Sea (B), Sea of Mar- mara (S), Aegean Sea (A), Mediterranean Sea (M). Reference Habitat Location 1. Ehrenberg (1843) Epizoic S 2. Hustedt (1930-1966)* Benthos S 3. Egemen et al. (1999) Planktonic A 4. Witkowski et al. (2000)* Benthos M 5. Aktan (2001)* Epilithic, Epipelic S 6. Koray (2001) Planktonic B,S,A,M 7. Polat & Işık (2002) Planktonic M 8. Türkoğlu & Koray (2002) Planktonic B 9. Balkıs (2003) Planktonic S 10. De Stefano & Marino (2003)* Epiphytic A 11. Balkıs (2004) Planktonic S 12. Aktan & Aykulu (2005)* Epipelic S 13. Balkıs (2005)* Benthos A 14. Baytut et al. (2005)* Benthos B 15. Aka & Polat (2006)* Planktonic M 16. De Stefano et al. (2006)* Epiphytic A 17. Çevik et al. (2008) Benthos M 18. Çolak Sabancı (2008)* Benthos A 19. De Stefano et al. (2008)* Epiphytic A 20. Sıvacı et al. (2008) Benthos B 21. Deniz & Taş (2009) Planktonic S 22. Gönülol et al. (2009) Epipelic B 23. Çolak Sabancı (2010)* Benthos A 24. Çolak Sabancı & Koray (2010)* Benthos A 25. Polge et al. (2010) Epipelic S 26. Altuğ et al. (2011) Planktonic S,A 27. Soylu et al. (2011) Epiphytic B 28. Çolak Sabancı (2012)* Benthos A 29. Özman-Say & Balkıs (2012) Planktonic M 30. Çolak Sabancı (2013)* Benthos A 31. Ağlaç & Balkıs (2014) Planktonic A 32. Aktan et al. (2014) Epipelic S 33. Balkıs & Toklu-Alıçlı (2014) Planktonic S 34. Blanco & Blanco (2014)* Benthos A 35. Pailles et al. (2014)* Fossil S 36. Taş (2014) Planktonic A 37. Baytut et al. (2016) Planktonic B 38. Kısa & Pabuççu (2016) Benthos, Planktonic B 39. Pennesi (2016)* Epiphytic A

Aquat Res 4(1), 88-115 (2021) • https://doi.org/10.3153/AR21008 Review Article

Table 1. Continue

40. Yıldız (2018)* Benthos S 41. Kaleli et al. (2017)* Epilithic B 42. Kaleli et al. (2018)* Epilithic B 43. Li et al. (2018)* Benthos A,M 44. Kaleli et al. (2019)* Epilithic, Epipsammic M 45. Kaleli et al. (2020)* Benthos M 46. Tüfekçi et al. (2008) Planktonic S 47. Topçu (2011) Planktonic A 48. Taşkın et al. (2019) Planktonic, Benthic B,S,A,M 49. Baytut et al. (2013)* Planktonic B 50. Taş & Okuş (2006) Planktonic B 51. Balkıs & Taş (2016) Planktonic S 52. Taş (2017)* Planktonic S 53. Taş & Becerril (2017)* Planktonic S 54. Ayaz et al. (2018) Benthic M 55. Eker-Develi & Kıdeyş (2003) Planktonic B 56. Feyzioğlu & Seyhan (2007) Planktonic B

Table 2. Most common species in the Turkish coastal waters. Taxon Citations Taxon Citations Cylindrotheca closterium 21 Thalassionema fraunfeldii 15 Nitzschia longissima 19 Striatella unipunctata 15 Coscinodiscus radiatus 17 Ditylum brightwelli 14 Thalassionema nitzschioides 17 Cerataulina pelagica 13 Pleurosigma normanii 17 Chaetoceros affinis 13 Licmophora abbreviata 16 Chaetoceros lorenzianus 13 Pseudosolenia calcar-avis 16 Hemiaulus hauckii 13 Achnanthes brevipes 15 Pseudo-nitzschia pungens 13 Grammatophora marina 15 Skeletonema costatum 13 Melosira moniliformis 15 Proboscia alata 12

Aquat Res 4(1), 88-115 (2021) • https://doi.org/10.3153/AR21008 Review Article

Conclusion should be noted that there have been no changes in the taxonomy of the genera and species, the nomenclature was updated Investigation of the marine diatoms started nearly two centu- in several taxa which were transferred or currently not in use ries ago in Turkish coasts, however, still, a lot of geographical anymore, therefore, more research should be carried out to spots were not investigated, and their diatom composition re- clarify the systematic problems of diatoms in Turkish coastal mains unknown. The list comprised many benthic diatoms as waters. well as the previously expressed planktonic forms, neverthe- less, showed that total taxa in the Turkish coasts were not en- tirely determined yet. The future studies should focus on the Etik Standart ile Uyumluluk benthic diatom composition with the help of LM and SEM to Conflict of interests: The authors declare that for this article they provide additional data for further implications. Morphologi- have no actual, potential or perceived conflict of interests. cal details of the benthic diatoms would enhance the knowledge not only on the taxonomy but also the biodiversity Ethics committee approval: Ethics committee approval is not and their geographical dispersal in the coastal waters like es- required for this study. tuarine areas, coastal lakes and lagoons. This paper brought Funding disclosure: This study is supported by the TUBITAK marine planktonic and benthic studies together and com- with a Project number of 119Y347 and by National Postdoctoral prised a dataset which could be comparative for the future Research Scholarship Program (2218). studies in Turkey and other regions. Although there were Acknowledgments: Authors express their appreciation to research- checklists on marine plankton, this study provided a list of ers who provided literature for this study. We thank the reviewers diatoms including both forms from the coasts of Turkey. for their comments, which greatly improved this study. However, many of the species were not illustrated, future Disclosure: - studies could extend the knowledge with accurate identification with the aid of the illustrated studies in the region. It

Updated Nomenclature List of updated species nomenclature (Taxa) cited in the previous studies (Cited Name), and their synonyms. Current Name Cited Name Achnanthes brevipes var. intermedia (Kützing) Cleve Achnanthes intermedia Kützing Achnanthes parvula Kützing Achnanthes brevipes var. parvula (Kützing) Cleve Achnanthes wellsiae (Reimer) Witkowski & Lange-Bertalot Astartiella welsiae (Reimer) Witkowski & Lange-Bertalot Actinocyclus octonarius var. ralfsii (Smith) Hendey Actinocyclus ralfsii (Smith) Ralfs Amphicocconeis disculoides (Hustedt) Stefano & Marino Cocconeis disculoides Hustedt Amphitetras antediluviana Ehrenberg Triceratium antediluvianum (Ehrenberg) Grunow Aneumastus tuscula (Ehrenberg) Mann & Stickle Navicula tuscula (Ehrenberg) Grunow Ardissonea formosa (Hantzsch) Grunow Synedra formosa Hantzsch Asterionellopsis glacialis (Castracane) Round Asterionella japonica Cleve Azpeitia nodulifera (Schmidt) Fryxell & Sims Coscinodiscus nodifer Schmidt Bacillaria socialis (Gregory) Ralfs Bacillaria paradoxa Gmelin Nitzschia paradoxa (Gmelin) Grunow Berkeleya scopulorum (Brébisson ex Kützing) Cox Navicula scopulorum Brébisson ex Kützing var. scopularum Biddulphia biddulphiana (Smith) Boyer Biddulphia pulchella Gray Brebissonia lanceolata (Agardh) Mahoney & Reimer Navicula lanceolata (Agardh) Kützing Caloneis amphisbaena var. subsalina (Donkin) Cleve Caloneis subsalina (Donkin) Hendey Catacombas gaillonii (Bory) D.M.Williams & Round Synedra gaillonii (Bory) Ehrenberg Chaetoceros atlanticus var. neopolitanus (Schröder) Hustedt Chaetoceros neapolitanus Schröder Chaetoceros neogracilis Van Landingham Chaetoceros gracilis Schütt Chaetoceros protuberans Lauder Chaetoceros didymus var. protuberans (Lauder) Gran & Yendo Chaetoceros willei Gran Chaetoceros affinis var. willei (Gran) Hustedt Cocconeis distans Gregory Cocconeis granulifera Greville Conticribra weissflogii (Grunow) Stachura-Suchoples & Williams Thalassiosira weissflogii (Grunow) Fryxell & Hasle Coronia decora (Brébisson) Ruck & Guiry Campylodiscus decorus Brébisson

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Coscinodiscopsis jonesiana (Greville) Sar & Sunesen Coscinodiscus jonesianus (Greville) Ostenfeld Coscinodiscus pavillardii Forti Coscinodiscus perforatus var. pavillardi (Forti) Hustedt Craticula cuspidata (Kützing) Mann Navicula cuspidata (Kützing) Kützing Craticula cuspidata var. heribaudii (Peragallo) J.Y.Li & Y.Z.Qi Navicula cuspidata var. heribaduii (Peragallo) Cleve Craticula halophila (Grunow) Mann Navicula cuspidata var. halophila Grunow Ctenophora pulchella (Ralfs ex Kützing) Williams & Round Synedra pulchella (Ralfs) Kützing Cylindrotheca closterium (Ehrenberg) Reimann & Lewin Nitzschia closterium (Ehrenberg) Smith Cymbopleura inaequalis (Ehrenberg) Krammer Cymbella inaequalis (Ehrenberg) Rabenhorst Cymbopleura naviculiformis (Auerswald ex Heiberg) Krammer Cymbella naviculiformis (Auerswald) Cleve Dactyliosolen fragilissimus (Bergon) Hasle Rhizosolenia fragilissima Bergon Dactyliosolen mediterraneus (H. Peragallo) H.Peragallo Leptocylindrus mediterraneus (H.Peragallo) Hasle Delphineis australis Watanabe, Tanaka, Reid, Kumada & Nagudo Rhaphoneis surirella var. australis (Petit) Grunow Delphineis surirella (Ehrenberg) Andrews Rhaphoneis surirella (Ehrenberg) Grunow Didymosphenia geminata (Lyngbye) Mart.Schmidt Gomphonema geminatum (Lyngbye) Agardh Diploneis crabro (Ehrenberg) Ehrenberg Navicula crabro (Ehrenberg) Kützing Ellerbeckia arenaria (D.Moore ex Ralfs) R.M.Crawford Melosira arenaria Moore ex Ralfs Encyonema leiblenii (Agardh) Silva, Jahn, Veiga Ludwig & Menezes Encyonema prostratum (Berkeley) Kützing Entomoneis alata (Ehrenberg) Ehrenberg Amhiprora alata (Ehrenberg) Kützing Entomoneis costata (Hustedt) Reimer Amphiprora costata Hustedt Entomoneis pulchra (Bailey) Reimer Amphiprora pulchra Bailey Eupyxidicula turris (Greville) S.Blanco & C.E.Wetzel Stephanopyxis turris (Greville) Ralfs Fallacia forcipata (Greville) Stickle & Mann Navicula forcipata Grevillei Fallacia forcipata var. densestriata (A.W.F.Schmidt) Gogorev Navicula forcipata Grevillei var. densestriata A.Schmidt Fogedia finmarchica (Cleve & Grunow) Witkowski, Metzeltin & Navicula finmarchica (Cleve & Grunow) Cleve Lange-Bertalot Fragilaria tabulata var. truncata (Greville) Lange-Bertalot Synedra fasciculata Ehrenberg var. truncata (Greville) Patrick Fragilariopsis rhombica (O’Meara) Hustedt Nitzschia angulata Hasle Grammatophora oceanica Ehrenberg Grammatophora oceanica (Smith) Hustedt Guinardia delicatula (Cleve) Hasle Rhizosolenia delicatula Cleve Guinardia striata (Stolterfoth) Hasle Rhizosolenia stolterfothii H. Peragallo Gyrosigma acuminatum (Kützing) Rabenhorst Gyrosigma spenceri (Quekett) Griffith & Henfrey Gyrosigma macrum (W.Smith) J.W.Griffith & Henfrey Pleurosigma macrum Smith Gyrosigma reversum (Gregory) Hendey Pleurosigma reversum Gregory Gyrosigma robustum (Grunow) Cleve Pleurosigma robustum Grunow Halamphora coffeiformis (C.Agardh) Levkov Amphora coffeaeformis (Agardh) Kützing Halamphora costata (W.Smith) Levkov Amphora costata Smith Halamphora exigua (Gregory) Levkov Amphora exigua Gregory Halamphora holsatica (Hustedt) Levkov Amphora holsatica Hustedt Halamphora normanii (Rabenhorst) Levkov Amphora normannii Rabenhorst Halamphora subholsatica (Krammer) Levkov Amphora subholsatica Krammer Halamphora veneta (Kützing) Levkov Amphora veneta Kützing Halamphora wisei (Salah) Álvarez-Blanco & Blanco Amphora turgida var. wisei Salah Helicotheca thamesis (Shrubsole) Ricard Streptotheca tamesis Shrubsole Hippodonta capitata (Ehrenberg) Lange-Bertalot, Metzeltin & Navicula capitata Ehrenberg Witkowski Iconella biseriata (Brébisson) Ruck & Nakov Surirella biseriata Brébisson Karayevia clevei (Grunow) Round & Bukhtiyarova Achnanthes clevei Grunow Karayevia rostrata (Hustedt) Bukhtiyarova Achnanthes clevei Grunow var. rostrata Hustedt Lyrella abrupta (Gregory) Mann Navicula abrupta (Gregory) Donkin Lyrella atlantica (Schmidt) Mann Navicula abrupta var. atlantica (Schmidt) Peragallo & Peragallo Lyrella lyra (Ehrenberg) Karajeva Navicula lyra Ehrenberg Lyrella lyroides (Hendey) Mann Navicula lyroides Hendey Mastogloia albertii A.Pavlov, E.Jovanovska, C.E.Wetzel, L.Ector & Mastogloia smithii var. amphicephala Grunow Z.Levkov Mastogloia lacustris (Grunow) Grunow Mastogloia smithii var. lacustris (Grunow) M.Voigt

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Melosira moniliformis (Müller) Agardh Melosira moniliformis (Müller) Agardh var. moniliformis Metacolioneis tumida (Brébisson ex Kützing) Blanco & Wetzel Scoliopleura tumida (Brébisson ex Kützing) Rabenhorst Microtabella interrupta (Ehrenberg) Round Striatella interrupta (Ehrenberg) Heiberg Navicula capitatoradiata H.Germain Navicula cryptocephala var. intermedia Grunow Navicula comoides (Dillwyn) Peragallo & Peragallo Navicula pseudocomoides Hendey Navicula cryptotenella Lange-Bertalot Navicula radiosa var. tenella (Brébisson ex Kützing) Van Heurck Navicula phyllepta Kützing Navicula lanceolata var. phyllepta (Kützing) Van Heurck Navicula ramosissima (Agardh) Cleve Navicula ramosissima var. ramosissima (Agardh) Cleve Navicula tripunctata (Müller) Bory Navicula gracilis Ehrenberg Navicula veneta Kützing Navicula cryptocephala var. veneta (Kützing) Rabenhorst Navicula viridula var. avenacea (Brébisson) Van Heurck Navicula avenacea (Brébisson et Godey) Brébisson ex Grunow Navicymbula pusilla (Grunow) Krammer Cymbella pusilla Grunow Neocalyptrella robusta (Norman ex Ralfs) Hernández-Becerril & Rhizosolenia robusta G.Norman ex Ralfs Meave del Castillo Odontidium hyemale (Roth) Kützing Diatoma hiemalis Heibe Olifantiella muscatinei (Reimer & Lee) Van de Vijver, Ector & Olifantiella pseudobiremis Riaux-Gobin Wetzel Pantocsekiella comensis (Grunow) Kiss & Ács Cyclotella comensis Grunow Pantocsekiella kuetzingiana (Thwaites) Kiss & Ács Cyclotella meneghiniana var. kutzingiana (Thwaites) Playfair Pantocsekiella ocellata (Pantocsek) Kiss & Ács Cyclotella ocellata Pantocsek Paraplaconeis placentula (Ehrenberg) Kulikovskiy & Lange- Navicula placentula (Ehrenberg) Kützing Bertalot Parlibellus berkeleyii (Kützing) E.J.Cox Navicula pseudocomoides Hendey Parlibellus plicatus (Donkin) Cox Navicula plicata Donkin Petroneis latissima (Gregory) Stickle & Mann Navicula latissima Gregory Pinnunavis elegans (Smith) Okuno Navicula elegans Smith Placoneis elginensis (Gregory) Cox Navicula elginensis (Gregory) Ralfs Plagiogramma minus (W.Gregory) Chunlian Li, Ashworth & Dimerogramma minor (Gregory) J.Ralfs Witkowski Plagiogrammopsis vanheurckii (Grunow) Hasle, Stosch & Plagiogramma van-heurckii Grunow Syvertsen Planothidium hauckianum (Grunow) Bukhtiyarova Achnanthes hauckiana Grunow Planothidium hauckianum var. rostratum (Schulz ex Hustedt) Achnanthes houckiana Grunow var. rostrata Shultz Andresen, Stoermer & Kreis, Jr. Planothidium lanceolatum (Brébisson ex Kützing) Lange-Bertalot Achnanthes lanceolata (Brébisson) Grunow Pleurosigma formosum var. dalmatica (dalmaticum) Grunow Pleurosigma decorum W. Smith var. dalmaticum sensu Peragallo Pleurosigma normanii Ralfs Pleurosigma affine Grunow Proboscia alata (Brightwell) Sundström Rhizolenia alata Brightwell Rhizosolenia alata Brightwell f. gracillima (Cleve) Gran Proboscia indica (H.Peragallo) Hernández-Becerril Proboscia alata f. indica (H.Peragallo) Gran Psammodictyon panduriforme (W.Gregory) D.G.Mann Nitzschia panduformis Gregory Psammodiscus nitidus (Gregory) Round & Mann Coscinodiscus nitidus Gregory Pseudo-nitzschia pungens (Grunow ex Cleve) Hasle Nitzschia pungens Grunow ex Cleve Pseudo-nitzschia seriata (Cleve) H.Peragallo Nitzshia seriata Cleve Pseudosolenia calcar-avis (Schultze) Sundström Rhizosolenia calcar-avis M.Schultze Rhizosolenia acuminata (H. Peragallo) H. Peragallo Rhizosolenia acuminata (H. Peragallo) Gran Rhizosolenia imbricata Brightwell Rhizolenia shrubsolei Cleve Rhizosolenia imbricata var. shrubsolei (Cleve) Schröder Rhopalodia constricta (W.Smith) Krammer Rhopalodia musculus var. constricta (Brébisson ex Smith) H. & M. Peragallo Sellaphora pupula (Kützing) Mereschkowsky Navicula pupula Kützing Seminavis eulensteinii (Grunow) D.B.Danielidis, K.Ford & Amphora angusta var. ventricosa (Gregory) Cleve D.Kennett Meuniera membranacea (Cleve) P.C.Silva Stauroneis membranacea (Cleve) Hustedt Staurophora amphioxys (Gregory) Mann Stauroneis gregorii Ralfs Stellarima stellaris (Roper) Hasle & Sims Coscinodiscus stellaris Roper

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Tabularia affinis var. acuminata (Grunow) Aboal Synedra tabulata var. acuminata (Grunow) Hustedt Tabularia fasciculata (Agardh) Williams & Round Synedra affinis Kützing Synedra fasciculata (Agardh) Kützing Synedra tabulata (C. Agardh) Kützing var. fasciculata (Kützing) Grunow Tetramphora intermedia (Cleve) Stepanek & Kociolek Amphora rhombica Kitton var. intermedia Cleve Tetramphora ostrearia (Brébisson) Mereschkowsky Amphora ostrearia Brébisson ex Kützing Thalassionema fraunfeldii (Grunow) Hallegraeff Thalassiothrix frauenfeldii (Grunow) Grunow Thalassiosira eccentrica (Ehrenberg) Cleve Coscinodiscus excentricus Ehrenberg Thalassiosira gravida Cleve Thalassiosira rotula Meunier Thalassiosira leptopus (Grunow) Hasle & Fryxell Coscinodiscus lineatus Ehrenberg Toxarium hennedyanum (Gregory) Pelletan Synedra hennedyana Gregory Toxarium undulatum Bailey Synedra undulata (Bailey) Gregory Triceratium pelagicum (Schröder) Sournia Biddulphia pelagica Schröder Trieres mobiliensis (Bailey) Ashworth & Theriot Biddulphia mobiliensis (Bailey) Grunow & Van Heurck Odontella mobiliensis (Bailey) Grunow Trieres regia (Schultze) Ashworth & Theriot Odontella regia (Schulze) Ostenfeld Tryblionella acuminata Smith Nitzschia acuminata (W.Smith) Grunow Tryblionella apiculata Gregory Nitzschia apiculata (Gregory) Grunow Tryblionella granulata (Grunow) Mann Nitzschia granulata Grunow Tryblionella navicularis (Brébisson) Ralfs Nitzschia navicularis (Brébisson ex Kützing) Grunow Tryblionella punctata Smith Nitzschia punctata (Smith) Grunow Ulnaria danica (Kützing) Compère & Bukhtiyarova Synedra ulna (Nitzsch) Ehrenberg var. danica (Kützing) Grunow Ulnaria ulna (Nitzsch) Compère Fragilaria ulna (Nitzsch) Lange-Bertalot Synedra ulna (Nitzsch) Ehrenberg

Checklist List of diatom species reported from previous 56 papers. Nomenclature updated, according to Guiry and Guiry (2020) and Kociolek et al. (2020). Systematics followed Round et al. (1990).

Coscinodiscophyceae Actinocyclus cuneiformis (Wallich) F.Gómez, Lu Wang & Senjie Lin 3 Actinocyclus normnanii f. subsalus (Juhlin-Dannfelt) Hustedt 37 Actinocyclus octonarius Ehrenberg 6,37,48 Actinocyclus octonarius var. ralfsii (Smith) Hendey 6 Actinocyclus subtilis (Gregory) Ralfs 5 Actinoptychus splendens (Shadbolt) Ralfs 6,48 Asterolampra grevillei (Wallich) Greville 6,7,29,31,36,48,51 Asterolampra marylandica Ehrenberg 6,7,15,29,31,36,48 Asterolampra vanheurckii Brun 6,48 Asteromphalus flabellatus (Brébisson) Greville 6,7,18,29,36,48 Asteromphalus heptactis (Brébisson) Ralfs 6,7,29,36,48 Asteromphalus hookeri Ehrenberg 6,15,29,48 Asteromphalus hyalinus Karsten 6,48 Aulacoseira granulata (Ehrenberg) Simonsen 14,25,37 Aulacoseira italica (Ehrenberg) Simonsen 25 Azpeitia nodulifera (Schmidt) Fryxell & Sims 3,6,48,56 Coscinodiscopsis jonesiana (Greville) Sar & Sunesen 6,48 Coscinodiscus asteromphalus Ehrenberg 6,48 Coscinodiscus centralis Ehrenberg 6,8,11,29,48,51 Coscinodiscus concinnus Smith 6,8,21,31,37,48,51,52 Coscinodiscus gigas Ehrenberg 6,48 Coscinodiscus granii Gough 3,6,8,9,11,48,51,52,56 Coscinodiscus janischii Schmidt 37

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Coscinodiscus marginatus Ehrenberg 6,8,48 Coscinodiscus oculus-iridis (Ehrenberg) Ehrenberg 6,48,51 Coscinodiscus pavillardii Forti 6,8,48 Coscinodiscus perforatus Ehrenberg 7,8,9,11,15,29,31,37,51 Coscinodiscus radiatus Ehrenberg 6,7,8,9,11,15,21,26,29,31,33,37,48, 50,51,52,56 Coscinodiscus wailesii Gran & Angst 6,37,48 Dactyliosolen antarcticus Castracane 6,29,48 Dactyliosolen blavyanus (H.Peragallo) Hasle 6,48 Dactyliosolen fragilissimus (Bergon) Hasle 6,8,9,11,33,46,48,50,51,52,56 Dactyliosolen mediterraneus H.Peragallo 6,29,31,48,51 Ellerbeckia arenaria (D.Moore ex Ralfs) R.M.Crawford 6 Eupyxidicula turris (Greville) S.Blanco & C.E.Wetzel 6,11,51 Gallionella asperula Ehrenberg 1 Guinardia cylindrus (Cleve) Hasle 6,9,48,51 Guinardia delicatula (Cleve) Hasle 6,8,11,31,48,50,51,52 Guinardia flaccida (Castracane) Peragallo 6,8,9,11,31,33,46,47,48,51 Guinardia striata (Stolterfoth) Hasle 6,8,11,17,29,31,47,48,50,51,52 Hyalodiscus scoticus (Kützing) Grunow 37 Melosira borreri Greville 6,8,48 Melosira dubia Kützing 2 Melosira moniliformis (Müller) Agardh 3,4,5,6,9,11,12,15,25,29,32,37,48,51,52 Melosira moniliformis var. octogona (Grunow) Hustedt 4 Melosira nummuloides Agardh 2,3,5,6,12,21,25,37,48,51,52,56 Melosira varians Agardh 22,25,37,56 Neocalyptrella robusta (Norman ex Ralfs) Hernández-Becerril & Meave del Castillo 3,6,31,48,51,52 Paralia sulcata (Ehrenberg) Cleve 6,25,29,48,51 Podosira hormoides (Montagne) Kützing 37 Proboscia alata (Brightwell) Sundström 3,8,9,11,29,31,33,46,51,52,55,56 Proboscia alata f. alata (Brightwell) Sundström 6,47,50 Proboscia alata f. gracillima (Brightwell) Sundström 6,50 Proboscia indica (H.Peragallo) Hernández-Becerril 6,47,50 Pseudosolenia calcar-avis (Schultze) Sundström 6,8,9,11,17,29,31,33,46,47,48,50,51,52,55,56 Rhizosolenia acuminata (H.Peragallo) H.Peragallo 6,48 Rhizosolenia bergonii H.Peragallo 6,48 Rhizosolenia castracanei H.Peragallo 6,31,48,52 Rhizosolenia faeroensis Ostenfeld 51 Rhizosolenia hebetata J.W.Bailey 11,33,51,52 Rhizosolenia hebetata var. semispina (Hensen) Gran 6,48,50 Rhizosolenia imbricata Brightwell 3,6,8,29,47,48,50,51 Rhizosolenia setigera Brightwell 6,8,9,11,33,46,47,48,51,52 Rhizosolenia styliformis Brightwell 6,11,29,31,46,47,48,50,51 Rhizosolenia temperei H.Peragallo 6,48,51 Stellarima stellaris (Roper) Hasle & Sims 6,48,51 Stephanopyxis palmeriana (Greville) Grunow 6,8,48 Triceratium dubium Brightwell 6,48 Triceratium favus Ehrenberg 6,48 Triceratium pelagicum (Schröder) Sournia 6,48 Mediophyceae Amphitetras antediluviana Ehrenberg 18 Ardissonea crystallina (C.Agardh) Grunow 5,18 Ardissonea crystallina var. dalmatica (Kützing) Mills 41,45 Ardissonea formosa (Hantzsch) Grunow 17 Bacteriastrum comosum Pavillard 6,48

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Bacteriastrum delicatulum Cleve 3,6,8,11,29,47,48,51 Bacteriastrum elegans Pavillard 6,29,31,48 Bacteriastrum elongatum Cleve 6,48,50 Bacteriastrum hyalinum Lauder 3,6,8,11,31,47,48,51,52 Bacteriastrum mediterraneum Pavillard 6,48 Bellerochea horologicalis Stosch 6,48 Biddulphia alternans (Bailey) Van Heurck 6,37,48,51 Biddulphia biddulphiana (Smith) Boyer 6,7,29,48 Biddulphia tridens (Ehrenberg) Ehrenberg 6,48 Cerataulina pelagica (Cleve) Hendey 6,8,9,11,29,31,33,37,46,48,51,52,56 Chaetoceros aequatorialis Cleve 52,53 Chaetoceros affinis Lauder 6,8,9,11,29,37,47,48,50,51,52,53,56 Chaetoceros anastomosans Grunow 6,48,50 Chaetoceros atlanticus Cleve 6,48 Chaetoceros atlanticus var. neopolitanus (Schröder) Hustedt 6,31 Chaetoceros borealis Bailey 6,48 Chaetoceros brevis Schütt 6,8,11,48,50,51,52,53,56 Chaetoceros coarctatus Lauder 6,48 Chaetoceros compressus Lauder 6,8,37,48,50,51,52 Chaetoceros constrictus Gran 6,8,9,11,37,48,50,51,52,53,56 Chaetoceros contortus Schütt 53 Chaetoceros costatus Pavillard 6,9,11,31,48,50,51,52,53 Chaetoceros crinitus Schütt 6,48,56 Chaetoceros criophilus Castracane 51 Chaetoceros curvisetus Cleve 6,8,9,11,37,48,50,51,52,53,55,56 Chaetoceros dadayi Pavillard 6,29,31,48 Chaetoceros danicus Cleve 6,8,9,11,29,31,48,50,51,52,53,56 Chaetoceros debilis Cleve 6,8,9,48,51,52,53 Chaetoceros decipiens Cleve 6,8,9,29,31,37,47,48,50,51,52,53,56 Chaetoceros densus (Cleve) Cleve 6,11,48,51 Chaetoceros diadema (Ehrenberg) Gran 6,9,11,31,48,50,51,52,53 Chaetoceros didymus Ehrenberg 11,29,31,33,48,51,52,53 Chaetoceros didymus var. anglicus (Grunow) Gran 6 Chaetoceros diversus Cleve 6,11,29,37,48,51 Chaetoceros eibenii Grunow 6,31,48 Chaetoceros fragilis Meunier 51 Chaetoceros holsaticus Schütt 6,8,9,11,31,48,50,51,52,53 Chaetoceros imbricatus Mangin 6,48 Chaetoceros laciniosus Schütt 6,8,9,11,48,50,51 Chaetoceros lauderi Ralfs ex Lauder 6,11,48,51,52,53,56 Chaetoceros lorenzianus f. forceps Meunier 53 Chaetoceros lorenzianus Grunow 6,8,9,11,29,37,46,47,48,50,51,52,53 Chaetoceros messanensis Castracane 6,8,31,48,50,51 Chaetoceros neogracilis Van Landingham 6,8,37,48 Chaetoceros pendulus Karsten 37 Chaetoceros perpusillus Cleve 6,48 Chaetoceros peruvianus Brightwell 6,9,11,29,31,37,48,50,51,52,53 Chaetoceros protuberans Lauder 6,8 Chaetoceros pseudocurvisetus Mangin 6,8,31,37,48 Chaetoceros rostratus Ralfs 6,11,29,31,33,48,51,53 Chaetoceros saltans Cleve 6,48 Chaetoceros similis Cleve 6,48,50,51 Chaetoceros simplex Ostenfeld 6,37,48,50,51 Chaetoceros socialis Lauder 6,8,11,31,37,48,51,52

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Chaetoceros subsecundus (Grunow ex Van Heurck) Hustedt 8,37,51 Chaetoceros tenuissimus Menuier 37,49 Chaetoceros teres Cleve 6,48,50,52,53 Chaetoceros tetrastichon Cleve 6,48,50 Chaetoceros tortissimus Gran 6,8,48,51,52,53 Chaetoceros vistulae Apstein 6,8,48 Chaetoceros vixvisibilis Schiller 56 Chaetoceros wighamii Brightwell 6,8,37,48,50,51,52,53,56 Chaetoceros willei Gran 6,50,51 Climacosphenia elongata Mereschkowsky 6,8,48 Climacosphenia moniligera Ehrenberg 6,7,15,17,29,36,48,50,52 Conticribra weissflogii (Grunow) Stachura-Suchoples & Williams 6,48 Cyclotella atomus Hustedt 37 Cyclotella caspia Grunow 56 Cyclotella choctawhatcheeana Prasad 37 Cyclotella meneghiniana Kützing 6,20,25,37 Cyclotella radiosa (Grunow) Lemmermann 25 Cyclotella striata (Kützing) Grunow 3 Cymatosira belgica Grunow 45 Cymatosira lorenziana Grunow 41,45 Detonula confervacea (Cleve) Gran 6,37,48,50,51,52 Detonula pumila (Castracane) Gran 6,11,48,50,51 Ditylum brightwelli (T.West) Grunow 6,8,9,11,31,33,37,46,47,48,50,51,52,56 Eucampia cornuta (Cleve) Grunow 6,31,48 Eucampia zodiacus Ehrenberg 6,31,29,47,48 Eunotogramma marinum (Smith) H.Peragallo & M.Peragallo 18,28,41,45 Helicotheca tamesis (Shrubsole) Ricard 6,9,11,33,48,51 Hemiaulus hauckii Grunow 6,8,9,29,31,33,37,47,48,50,51,52,56 Hemiaulus membranaceus Cleve 6,48,51 Hemiaulus sinensis Greville 6,11,31,48,51,52,56 Lauderia annulata Cleve 6,9,11,33,47,48,50,51,52 Leptocylindrus danicus Cleve 6,8,9,33,37,46,47,48,50,51,52,56 Leptocylindrus minimus Gran 6,8,11,29,37,47,48,50,51,52 Lindavia comta (Kützing) Nakov, Guillory, Julius, Theriot & Alverson 38 Lindavia glomerata (H.Bachmann) Adesalu & Julius 37 Lithodesmium undulatum Ehrenberg 6,29,31,48 Neohuttonia reichardtii (Grunow) Hustedt 45 Odontella aurita (Lyngbye) Agardh 6,15,29,41,48 Odontella obtusa Kützing 37 Odontella sinensis (Greville) Grunow 51 Pantocsekiella comensis (Grunow) Kiss & Ács 20 Pantocsekiella kuetzingiana (Thwaites) Kiss & Ács 27,37 Pantocsekiella ocellata (Pantocsek) Kiss & Ács 22,25,27 Plagiogrammopsis vanheurckii (Grunow) Hasle, Stosch & Syvertsen 6,48 Pleurosira laevis (Ehrenberg) Compère 25 Skeletonema costatum (Greville) Cleve 6,8,9,11,31,32,33,46,47,48,50,51,56 Skeletonema dohrnii Sarno & Kooistra 37 Skeletonema marinoi Sarno & Zingone 49,52 Skeletonema menzelii Guillard, Carpenter & Reimann 6,48 Stephanodiscus hantzschii Grunow 37 Stephanodiscus minutulus (Kützing) Cleve & Möller 37 Thalassiosira allenii Takano 6,8,9,11,21,48,50,51 Thalassiosira angulata (Gregory) Hasle 6,9,11,37,48,51 Thalassiosira angustelineata (Schmidt) Fryxel & Hasle 6,8,9,11,21,33,37,48,51,56

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Thalassiosira antarctica Comber 51 Thalassiosira antiqua (Grunow) Proschkina-Lavrenko 37 Thalassiosira decipiens (Grunow) Jörgensen 6,8,21,48,56 Thalassiosira eccentrica (Ehrenberg) Cleve 6,8,11,25,37,50,51 Thalassiosira fragilis G.Fryxell 51 Thalassiosira gravida Cleve 6,8,9,11,21,31,33,37,48,51,52,56 Thalassiosira hyalina (Grunow) Gran 6,48,51 Thalassiosira leptopus (Grunow) Hasle & Fryxell 6,8,11,48,51 Thalassiosira minima Gaarder 52 Thalassiosira nordenskioeldii Cleve 6,8,9,11,29,37,48,51,52,56 Thalassiosira parva Proschkina-Lavrenko 37 Thalassiosira subtilis (Ostenfeld) Gran 6,8,48 Thalassiosira tenera Proschkina-Lavrenko 6,48 Toxarium hennedyanum (Gregory) Pelletan 6,48 Toxarium undulatum Bailey 3,6,7,8,17,29,36,37,48,50,52 Trieres mobiliensis (Bailey) Ashworth & Theriot 6,7,15,18,29,31,36,37,48 Trieres regia (Schultze) Ashworth & Theriot 6,48 Bacillariophyceae Achnanthes bacillaris Ehrenberg 1 Achnanthes brevipes var. angustata Greville 18,20 Achnanthes brevipes var. brevipes Agardh 3,4,5,6,9,11,12,18,25,28,33,37,38,48,51 Achnanthes brevipes var. intermedia (Kützing) Cleve 17,18,25,28 Achnanthes coarctata (Brébisson ex W.Smith) Grunow 37 Achnanthes danica (Flögel) Grunow 45 Achnanthes kuwaitensis Hendey 18 Achnanthes lacunarum Hustedt 25 Achnanthes longipes Agardh 3,6,8,18,28,36,37,48,56 Achnanthes parvula Kützing 17,18,25,28 Achnanthes pseudobrevipes Aleem 18 Achnanthes wellsiae (Reimer) Witkowski & Lange-Bertalot 25 Achnanthidium affine (Grunow) Czarnecki 38 Achnanthidium minutissimum (Kützing) Czarnecki 20 Adlafia brockmannii (Hustedt) Bruder & Hinz 37 Amphicocconeis debesi (Hustedt) De Stefano 16 Amphicocconeis disculoides (Hustedt) Stefano & Marino 3,10 Amphipleura pellucida (Kützing) Kützing 20 Amphiprora angustata Hendey 3 Amphora angustata Cleve 3 Amphora arenicola Grunow ex Cleve 48,56 Amphora bigibba var. interrupta (Grunow) Cleve 41 Amphora binodis Gregory 18 Amphora cingulata Cleve 37 Amphora commutata Grunow 20,22,25 Amphora cymbamphora Cholnoky 41,44,45 Amphora delicatissima Krasske 5,12,51 Amphora eximia J.R.Carter 37 Amphora graeffeana Hendey 41 Amphora hamata Heiden 44 Amphora helenensis Giffen 40 Amphora laevis Gregory 37 Amphora marina Smith 6,41,48 Amphora ocellata Donkin 37 Amphora ovalis (Kützing) Kützing 5,6,12,18,20,25,27,29,32,37,51,56 Amphora pediculus (Kützing) Grunow 20,25,37

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Amphora proteus Gregory 18,28,41,44 Aneumastus tuscula (Ehrenberg) Mann & Stickle 5,12,32,51 Anomoeoneis sphaerophora (Kützing) Pfitzer 17,20,22,44 Anomoeoneis sphaerophora var. sculpta (Ehrenberg) Müller 17 Anorthoneis exentrica (Donkin) Grunow 5,12,51 Anorthoneis vortex Sterrenburg 45 Asterionella bleakeleyii Smith 11,51 Asterionella formosa Hassal 37 Asterionella notata Grunow 6 Asterionellopsis glacialis (Castracane) Round 6,7,8,11,15,29,36,48,50,51,52,56 Bacillaria paxillifera (Müller) T.Marsson 3,6,7,8,11,15,17,20,26,29, 31,37,48,51 Bacillaria socialis (Gregory) Ralfs 18 Berkeleya antarctica Grunow 41 Berkeleya micans (Lyngbye) Grunow 40,41 Berkeleya obtusa (Greville) Grunow 40 Berkeleya rutilans (Trentepohl ex Roth) Grunow 41 Berkeleya scopulorum (Brébisson ex Kützing) Cox 18,28 Berkeleya sparsa M.Mizuno 40,41 Biremis lucens (Hustedt) Sabbe, Witkowski & Vyverman 40 Brachysira aponina Kützing 44 Brachysira estonarium Witkowski, Lange-Bertalot & Metzeltin 44,45 Brebissonia lanceolata (Agardh) Mahoney & Reimer 6,8,20 Caloneis amphisbaena (Bory) Cleve 20,25 Caloneis amphisbaena var. subsalina (Donkin) Cleve 3,37 Caloneis bacillum (Grunow) Cleve 37 Caloneis clevei (Lagerstedt) Cleve 20 Caloneis liber (Smith) Cleve 45 Caloneis linearis (Cleve) Boyer 18,41 Caloneis permagna (Bailey) Cleve 37 Caloneis silicula (Ehrenberg) Cleve 22,27 Caloneis undulata (W.Gregory) Krammer 37 Caloneis westii (W.Smith) Hendey 20,37 Campylodiscus bicostatus W.Smith ex Roper 20 Campylodiscus echeneis Ehrenberg ex Kützing 48 Campylodiscus fastuosus Ehrenberg 3 Catacombas gaillonii (Bory) D.M.Williams & Round 18,25,48 Catenula adhaerens (Mereschkowsky) Mereschkowsky 45 Chamaepinnularia alexandrowiczii Witkowski, Lange-Bertalot & Metzeltin 44 Chamaepinnularia clamans (Hustedt) Witkowski, Lange-Bertalot & Metzeltin 40,41 Chamaepinnularia hassiaca (Krasske) Cantonati & Lange-Bertalot 38 Cocconeis costata Gregory 18 Cocconeis diaphana Smith 45 Cocconeis dirupta Gregory 45 Cocconeis dirupta var. flexella (Janisch & Rabenhorst) Grunow 18,28 Cocconeis disculus (Schumann) Cleve 5 Cocconeis distans Gregory 16,18 Cocconeis guttata Hustedt & Aleem 41 Cocconeis irregularis (P.Schulz) Witkowski 41 Cocconeis latecostata Hustedt 41 Cocconeis margaritifera Ehrenberg 1 Cocconeis notata Petit 2 Cocconeis pediculus Ehrenberg 5,18,22,25,27,28,37 Cocconeis pellucida Grunow 18

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Cocconeis pelta Schmidt 45 Cocconeis peltoides Hustedt 45 Cocconeis placentula Ehrenberg 17,18,28,37,38,44 Cocconeis placentula var. euglypta (Ehrenberg) Grunow 20 Cocconeis placentula var. rouxii (Héribaud-Joseph & Brun) Cleve 25 Cocconeis pseudo-marginata Gregory 18,23,28,48 Cocconeis scutellum Ehrenberg 5,6,8,12,18,19,28,32,37,44,48,51 Cocconeis scutellum var. parva (Grunow) Cleve 19 Cocconeis scutellum var. posidoniae M.De Stefano, D.Marino & L.Mazzella 19 Cocconeis speciosa Gregory 3 Coronia decora (Brébisson) Ruck & Guiry 6,17,37,48 Cosmioneis lundstroemii (Cleve) D.G.Mann 37 Cosmioneis pusilla (Mann) Stickle 28 Craspedostauros decipiens (Hustedt) E.J.Cox 2 Craticula cuspidata (Kützing) Mann 6,22,27,28 Craticula cuspidata var. heribaudii (Peragallo) J.Y.Li & Y.Z.Qi 18 Craticula halophila (Grunow) Mann 18 Ctenophora pulchella (Ralfs ex Kützing) Williams & Round 18,28,37 Cylindrotheca closterium (Ehrenberg) Reimann & Lewin 3,5,6,7,8,9,11,12,15,17,21,25,26,29,31,32,33,3 6,37,38,48,51,52,56 Cymatopleura elliptica ( Brébisson) W.Smith 20,37 Cymatopleura solea (Brébisson) W.Smith 20,22,37 Cymbella affinis Kützing 18,20,27,28,37,38 Cymbella cistula (Ehrenberg) Kirchner 27,37,38 Cymbella cymbiformis Agardh 14,37 Cymbella cymbiformis var. nonpunctata Fontell 37 Cymbella helvetica Kützing 37,38 Cymbella hustedtii Krasske 37 Cymbella lanceolata (C.Agardh) C.Agardh 6,8,20 Cymbella turgidula Grunow 6 Cymbella ventricosa Kützing 27 Cymbopleura inaequalis (Ehrenberg) Krammer 14 Cymbopleura naviculiformis (Auerswald ex Heiberg) Krammer 20 Delicata delicatula (Kützing) Krammer 37 Delphineis australis Watanabe, Tanaka, Reid, Kumada & Nagudo 18,28 Delphineis karstenii (Boden) G.Fryxell 18,44 Delphineis minutissima (Hustedt) Simonsen 41 Delphineis surirella (Ehrenberg) Andrews 45 Denticula subtilis Grunow 41 Diatoma moniliformis Kützing 37 Diatoma tenuis C.Agardh 37 Diatoma vulgaris Bory 6,27,37,38 Didymosphenia geminata (Lyngbye) Mart.Schmidt 6,56 Dimeregramma acutum Hustedt 34 Diplomenora cocconeiformis (Schmidt) Blazé 45 Diploneis aestuari Hustedt 41 Diploneis bombus (Ehrenberg) Ehrenberg 4,6,9,11,29,33,44,48,51 Diploneis chersonensis (Grunow) Cleve 17,37,41,48 Diploneis crabro (Ehrenberg) Ehrenberg 6,8,48 Diploneis decipiens Cleve-Euler 48 Diploneis interrupta (Kützing) Cleve 20 Diploneis notabilis (Greville) Cleve 18 Diploneis ovalis (Hilse) Cleve 20 Diploneis parma Cleve 20

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Diploneis pseudovalis Hustedt 4,22,27 Diploneis smithii (Brébisson) Cleve 37 Diploneis stroemii Hustedt 41 Encyonema leibleinii (Agardh) Silva, Jahn, Veiga Ludwig & Menezes 22,27,37 Encyonema minutum (Hilse) Mann 22,27,37 Encyonema silesiacum (Bleisch) D.G.Mann 22 Encyonopsis cesatii (Rabenhorst) Krammer 37 Entomoneis alata (Ehrenberg) Ehrenberg 5,6,12,18,22,48,51 Entomoneis calixasini Paillès, Blanc-Valleron & Poulin 35 Entomoneis costata (Hustedt) Reimer 25,48 Entomoneis gigantea (Grunow) Nizamuddin 6,15,29,48 Entomoneis ornata (Bailey) Reimer 48 Entomoneis paludosa (W.Smith) Reimer 22,48 Entomoneis pulchra (Bailey) Reimer 3 Eolimna minima (Grunow) Lange Bertalot 37 Epithemia argus (Ehrenberg) Kützing 20 Epithemia gibba (Ehrenberg) Kützing 20 Epithemia muelleri Fricke 17,48 Epithemia sorex Kützing 20,22,27,37 Eucocconeis flexella (Kützing) Meister 20 Eunotia arcus Ehrenberg 37 Eunotia bigibba Kützing 37 Eunotia septentrioralis Østrup 37 Fallacia clepsidroides Witkowski 4 Fallacia cryptolyra (Brockmann) Stickle & D.G.Mann 25 Fallacia florinae (M.Møller) Witkowski 40 Fallacia forcipata (Greville) Stickle & Mann 18,28,37,41 Fallacia forcipata var. densestriata (A.W.F.Schmidt) Gogorev 18,28 Fallacia nyella Hustedt 41 Fallacia pseudony (Hustedt) Mann 41,45 Fallacia pygmaea (Kützing) Stickle & D.G.Mann 37 Fallacia schaeferae (Hustedt) Mann 44,45 Fallacia subforcipata (Hustedt) D.G.Mann 41 Fogedia finmarchica (Cleve & Grunow) Witkowski, Metzeltin & Lange-Bertalot 18 Fogedia giffeniana (Foged) Witkowski, Lange-Bertalot, Metzeltin & Bafana 41 Fragilaria amphicephaloides Lange-Bertalot 37 Fragilaria capucina Desmazières 37 Fragilaria crotonesis Kitton 6,37 Fragilaria eichornii Witkowski & Lange-Bertalot 41 Fragilaria gracillima Mayer 37 Fragilaria inflata Pantocsek 37 Fragilaria striatula Lyngbye 48 Fragilaria tabulata var. truncata (Greville) Lange-Bertalot 25 Fragilaria vaucheriae (Kützing) J.B.Petersen 37,38 Fragilariopsis atlantica Paasche 6,48 Fragilariopsis cylindrus (Grunow ex Cleve) Helmcke & Krieger 6,51 Fragilariopsis oceanica (Cleve) Hasle 5,12,48,51 Fragilariopsis rhombica (O’Meara) Hustedt 56 Frustulia creuzburgensis (Krasske) Hustedt 37 Frustulia rhomboides (Ehrenberg) De Toni 20 Gedaniella flavovirens (H.Takano) Chunlian Li, A.Witkowski & M.P.Ashworth 43 Gedaniella guenter-grassi (Witkowski & Lange-Bertalot) Chunlian Li, S.Sato & 40 Witkowski Gedaniella mutabilis Chunlian Li & Witkowski 40

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Geisleria acceptata (Hustedt) Lange-Bertalot & Metzeltin 25 Glyphodesmis distans (W.Gregory) Grunow 41 Gomphonema acuminatum Ehrenberg 20 Gomphonema affine Kützing 37 Gomphonema angustatum (Kützing) Rabenhorst 20,25 Gomphonema capitatum Ehrenberg 22 Gomphonema helveticum Brun 27 Gomphonema minutum (C.Agardh) C.Agardh 37 Gomphonema olivaceum (Hornemann) Brébisson 20,27,37 Gomphonema parvulum (Kützing) Kützing 22,27,38 Gomphonema subtile Ehrenberg 37 Gomphonema truncatum Ehrenberg 37 Gomphonemopsis obscura (Krasske) Lange-Bertalot 40,41 Grammatophora angulosa Ehrenberg 18,28,41,44,48,51 Grammatophora angulosa var. mediterranea Grunow 45 Grammatophora arcuata Ehrenberg 18,34 Grammatophora macilenta W.Smith 41 Grammatophora marina (Lyngbye) Kützing 5,6,8,9,11,15,18,29,32,36,37,48,50,51,56 Grammatophora oceanica Ehrenberg 18,28,41,48 Grammatophora oceanica var. macilenta (Smith) Grunow 18 Grunowia solgensis (A.Cleve) Aboal 37 Gyrosigma acuminatum (Kützing) Rabenhorst 6,8,18,20,25,37,38 Gyrosigma attenuatum (Kützing) Robenhorst 6,29,48 Gyrosigma balticum (Ehrenberg) Rabenhorst 6,7,15,17,18,28,29,48 Gyrosigma eximium (Thwaites) Boyer 17,37,44 Gyrosigma fasciola (Ehrenberg) Griffith & Henfrey 5,6,9,11,12,25,32,37,48,51 Gyrosigma hippocampus Ehrenberg 3,6 Gyrosigma macrum (W.Smith) J.W.Griffith & Henfrey 6 Gyrosigma obscurum (W.Smith) Griffith & Henfrey 25,37 Gyrosigma peisone (Grunow) Hustedt 25 Gyrosigma reversum (Gregory) Hendey 13,33,48,51 Gyrosigma robustum (Grunow) Cleve 18 Gyrosigma scalproides (Rabenhorst) Cleve 25 Gyrosigma strigilis (Smith) Cleve 27 Gyrosigma tenuissimum (W.Smith) Griffith & Henfrey 6,15,17,29,41,48 Halamphora acutiuscula (Kützing) Levkov 37,44 Halamphora capitata (Hagelstein) A.Blanco & S.Blanco 40 Halamphora coffeiformis (C.Agardh) Levkov 5,12,18,20,25,37,41,51 Halamphora costata (W.Smith) Levkov 5,12,51 Halamphora exigua (Gregory) Levkov 5,12,18,28,37,51 Halamphora holsatica (Hustedt) Levkov 20,37 Halamphora hyalina (Kützing) Rimet & R.Jahn 6,48 Halamphora kolbei (Aleem) A.Blanco & S.Blanco 40 Halamphora normanii (Rabenhorst) Levkov 20,37 Halamphora pseudohyalina (Simonsen) J.G.Stepanek & Kociolek 41 Halamphora staurophora (Juhlin-Dannfelt) Alvarez Blanco & S.Blanco 41 Halamphora subholsatica (Krammer) Levkov 4,44 Halamphora tenerrima (Aleem & Hustedt) Levkov 40,44 Halamphora turgida (Gregory) Levkov 28,37,41 Halamphora veneta (Kützing) Levkov 18,37 Halamphora wisei (Salah) Álvarez-Blanco & Blanco 18,34 Hannaea arcus (Ehrenberg) Patrick 6,37,56 Hantzschia amphioxys (Ehrenberg) Grunow 5,12,18,20,28,32,37,51 Haslea britannica (Hustedt & Aleem) Witkowski, Lange-Bertalot & Metzeltin 41

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Haslea nautica (Cholnoky) Giffen 41 Haslea ostrearia (Gaillon) Simonsen 48 Haslea spicula (Hickie) Bukhtiyarova 38,48 Hippodonta capitata (Ehrenberg) Lange-Bertalot, Metzeltin & Witkowski 20 Iconella biseriata (Brébisson) Ruck & Nakov 17,22 Karayevia amoena (Hustedt) Bukhtiyarova 2 Karayevia clevei (Grunow) Round & Bukhtiyarova 18,28 Karayevia rostrata (Hustedt) Bukhtiyarova 25 Licmophora abbreviata Agardh 5,6,7,8,9,11,12,18,29,31,34,36,48,50,51,52 Licmophora dalmatica (Kützing) Grunow 40 Licmophora debilis (Kützing) Grunow ex Van Heurck 40,41 Licmophora ehrenbergii (Kützing) Grunow 6,18,28,37,48,56 Licmophora ehrenbergii f. grunowii (Mereschkowsky) Hustedt 18,45 Licmophora flabellata (Greville) Agardh 6,8,18,28,41,48,51 Licmophora gracilis (Ehrenberg) Grunow 6,8,11,18,28,48 Licmophora hyalina (Kützing) Grunow 18,28 Licmophora lyngbyei (Kützing) Grunow ex Van Heurck 3,17,37 Licmophora paradoxa (Lyngbye) Agardh 5,6,8,12,32,48,51 Lyrella abrupta (Gregory) Mann 18,28,37,41 Lyrella atlantica (Schmidt) Mann 18 Lyrella clavata (W.Gregory) D.G.Mann 41 Lyrella lyra (Ehrenberg) Karajeva 5,12,13,18,32,33,48,51 Lyrella lyroides (Hendey) Mann 18 Mastogloia acutiuscula Grunow 44 Mastogloia albertii A.Pavlov, E.Jovanovska, C.E.Wetzel, L.Ector & Z.Levkov 17,18 Mastogloia angulata Lewis 6,17,44,48 Mastogloia aquilegiae Grunow 18,30 Mastogloia baldjikiana Grunow 30 Mastogloia belaensis Voigt 44 Mastogloia binotata (Grunow) Cleve 18,28,30,34,44 Mastogloia braunii Grunow 18,20,28,48 Mastogloia crucicula (Grunow) Cleve 44,45 Mastogloia crucicula var. alternans Zanon 44 Mastogloia danseyi (Thwaites) Thwaites ex Smith 48 Mastogloia emarginata Hustedt 45 Mastogloia exigua Lewis 18,37 Mastogloia fimbriata (Brightwell) Cleve 6,39,48 Mastogloia gieskeii Cholnoky 41 Mastogloia grevillei W.Smith 48 Mastogloia grunowii Schmidt 18,30 Mastogloia ignorata Hustedt 30,41 Mastogloia labuensis Cleve 17 Mastogloia lacustris (Grunow) Grunow 18,48 Mastogloia lanceoalata Thwaites ex Smith 18,28,44 Mastogloia ovalis A.Schmidt 45 Mastogloia paradoxa Grunow 30,41 Mastogloia pumila (Grunow) Cleve 2,18,20,28,30,37,41 Mastogloia pusilla Grunow 40 Mastogloia pusilla var. subcapitata Hustedt 40,41 Mastogloia similis Hustedt 30,41 Mastogloia smithii Thwaites ex Smith 17,18,20,22,28,37 Mastogloia splendida (Gregory) Peragallo 6 Mastogloia urvae Witkowski 40,48 Mastogloia vasta Hustedt 30,48

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Meloneis mimallis Louvrou, Danielidis & Economou-Amilli 45 Metacolioneis tumida (Brébisson ex Kützing) Mann 18 Microtabella interrupta (Ehrenberg) Round 6,8,48 Nanofrustulum shiloi (J.J.Lee, Reimer & McEnery) Round, Hallsteinsen & Paasche 43 Navicula abrupta var. rattrayi (Pantocsek) Peragallo & Peragallo 18 Navicula arenaria Donkin 18,28 Navicula arenaria var. rostellata Lange-Bertalot 45 Navicula cancellata Donkin 6,18,48 Navicula capitatoradiata H.Germain 18 Navicula cari Ehrenberg 20,27 Navicula cincta (Ehrenberg) Ralfs 18,28,37,38 Navicula cryptocephala Kützing 5,12,18,20,25,28,32,51 Navicula cryptotenella Lange-Bertalot 18,25,28,37,44 Navicula decussata Ehrenberg 1 Navicula digitoradiata (Gregory) Ralfs 18 Navicula directa (W.Smith) Ralfs 5,12,51 Navicula distans (Smith) Ralfs 3,48 Navicula exigua W.Gregory 25 Navicula formenterae Cleve 18 Navicula germanopolonica Witkowski & Lange-Bertalot 40 Navicula globosa F.Meister 37 Navicula gregaria Donkin 27,37 Navicula grevilleana Hendey 18 Navicula inornata Grunow 18 Navicula johanrossi Giffen 28 Navicula libonensis Schoeman 37 Navicula lusoria Giffen 45 Navicula menaiana Hendey 18,48 Navicula menisculus Schumann 5,12,20,38,51 Navicula metareichardtiana Lange-Bertalot & Kusber 44 Navicula palpepralis Brébisson ex W.Smith 5,12,32,41,51 Navicula parapontica Witkowski, Kulikovskiy, Nevrova & Lange-Bertalot 40,41 Navicula pavillardii Hustedt 40 Navicula pennata Schmidt 6,8,18,37,48 Navicula pennata var. pontica Mereschowsky 37 Navicula phyllepta Kützing 18,37 Navicula pontica (Mereschkowksy) A.Witkowski, M.Kulikovskiy, E.Nevrova & 41 Lange-Bertalot Navicula pseudosilicula Hustedt 18 Navicula radiosa Kützing 20,22,25,27 Navicula ramosissima (Agardh) Cleve 18,25,44,48 Navicula ramosissima var. mollis (W. Smith) Hendey 18 Navicula ramosissima var. mucosa (Aleem) Hendey 5,12,18,28,32,51 Navicula resecta J.R.Carter 37 Navicula rostellata Kützing 5,12,38,51 Navicula ryhncocephala Kützing 27,37 Navicula salinarum Grunow 18,22,25,37 Navicula scabriuscula (Cleve & Grove) Mereschkowsky 28 Navicula sigma Ehrenberg 37 Navicula slesvicensis Grunow 20 Navicula subagnita Proschkina Lavrenko 40,41,44 Navicula subinflata Grunow 18 Navicula tenella Brébisson ex Kützing 5,12,25,51 Navicula transitans Cleve 29,48

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Navicula tripunctata (Müller) Bory 5,12,18,22,25,27,28,51 Navicula tripunctata var. schizonemoides (Van Heurck) R.M.Patrick 25 Navicula trivialis Lange-Bertalot 37 Navicula veneta Kützing 18,22,37 Navicula viridula (Kützing) Ehrenberg 38 Navicula viridula var. avenacea (Brébisson) Van Heurck 18 Navicula zostereti Grunow 6,8,48 Navicymbula pusilla (Grunow) Krammer 18,28,38,44 Navicymbula pusilla var. lata Krammer 40,44 Neidiopsis levanderi (Hustedt) Lange-Bertalot & Metzeltin 37 Neidium dubium (Ehrenberg) Cleve 37 Neosynedra provincialis (Grunow) Williams & Round 40,41 Nitzschia acicularis (Kützing) Smith 3,22,37 Nitzschia aequorea Hustedt 45 Nitzschia amabilis Suzuki 41,45 Nitzschia amphibia Grunow 38 Nitzschia amplectens Hustedt 37 Nitzschia angularis Smith 18,28 Nitzschia bilobata Smith 3 Nitzschia brevissima Grunow 20 Nitzschia capitellata Hustedt 2 Nitzschia clausii Hantzsch 20,37,41 Nitzschia communata Grunow 25,38 Nitzschia compressa var. balatonis (Grunow) Lange-Bertalot 24 Nitzschia constricta f. parva Grunow 18 Nitzschia dissipata (Kützing) Rabenhorst 22,27,37,38 Nitzschia elegantula Grunow 44 Nitzschia flexa Schumann 37 Nitzschia fonticola (Grunow) Grunow 22,38 Nitzschia fontifuga Cholnoky 44 Nitzschia frustulum (Kützing) Grunow 5,12,18,28,51 Nitzschia frustulum var. perpusilla (Rabenhorst) Van Heurck 5,12 Nitzschia fusiformis Grunow 41 Nitzschia improvisa Simonsen 44 Nitzschia incerta (Grunow) M.Peragallo 37 Nitzschia inconspicua Grunow 44 Nitzschia insignis W.Gregory 26 Nitzschia intermedia Hantzsch 18,28 Nitzschia kuetzingiana Hilse 25 Nitzschia linearis (Agardh) Smith 18,20,28,37 Nitzschia linearis var. subtilis Hustedt 24 Nitzschia longissima (Brébisson ex Kützing) Grunow 3,5,6,7,8,9,11,12,15,18,21,29,36,37,48,50,51,52, 56 Nitzschia lorenziana Grunow 6,18,28,29,33,48,51 Nitzschia microcephala Grunow 24 Nitzschia nana Grunow 37 Nitzschia nanodissipata Chunlian Li & Witkowski 45 Nitzschia navis-varingica Lundholm & Moestrup 54 Nitzschia obtusa Smith 18,37 Nitzschia ovalis Arnott 37,38 Nitzschia palea (Kützing) Smith 5,12,20,27,32,37,38,51 Nitzschia prolongata Hustedt 40 Nitzschia recta Hantzsch ex Rabenhorst 37 Nitzschia rectilonga Takano 21,50,51

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Nitzschia rectirobusta Lange-Bertalot 24 Nitzschia reversa W.Smith 41 Nitzschia scalpelliformis Grunow 24,28 Nitzschia sicula (Castracane) Hustedt 6,48 Nitzschia sigma (Kützing) Smith 6,7,8,17,18,20,29,33,37,50,51 Nitzschia sigmoidea (Nitzsch) Smith 3,15,17,26,29,33,37,48,51 Nitzschia socialis Gregory 18 Nitzschia socialis var. massiliensis Grunow 18,40 Nitzschia supralitorea Lange-Bertalot 24 Nitzschia tryblionella Hantzsch 20,37 Nitzschia umbonata (Ehrenberg) Lange-Bertalot 22,37 Nitzschia valdestriata Aleem & Hustedt 44,45 Nitzschia vermicularis (Kützing) Lange-Bertalot 24 Nitzschia vidovichii (Grunow) Grunow 24 Odontidium hyemale (Roth) Kützing 56 Olifantiella muscatinei (Reimer & Lee) Van de Vijver, Ector & Wetzel 42 Paraplaconeis placentula (Ehrenberg) Kulikovskiy & Lange-Bertalot 20,22,32 Parlibellus bennikei Witkowski 28 Parlibellus berkeleyi (Kützing) Cox 18,40,41 Parlibellus calvus Witkowski, Metzeltin & Lange-Bertalot 40 Parlibellus delognei (Van Heurck) E.J.Cox 41 Parlibellus plicatus (Donkin) Cox 17 Petrodictyon gemma (Ehrenberg) Mann 6,18,28,29,31,48,51,52 Petroneis humerosa (Brébisson ex Smith) Stickle & Mann 5,12,20,32,48,51 Petroneis latissima (Gregory) Stickle & Mann 3 Phaeodactylum tricornutum Bohlin 6,48 Pinnularia aestuarii Cleve 37 Pinnularia bipectinalis (Schumann) Greguss 37 Pinnularia borealis Ehrenberg 37 Pinnularia claviculus (Gregory) Rabenhorst 37 Pinnularia gentilis (Donkin) Cleve 37 Pinnularia interrupta W.Smith 22 Pinnularia lundii Hustedt 37 Pinnularia microstauron (Ehrenberg) Cleve 37 Pinnunavis elegans (Smith) Okuno 3 Placoneis amphibola Cleve 25 Placoneis clementis (Grunow) Cox 20 Placoneis elginensis (Gregory) Cox 27,38 Placoneis gastrum (Ehrenberg) Mereschkowsky 38 Placoneis placentula (Ehrenberg) Mereschkowsky 20,32,51 Plagiogramma minus (Gregory) Chunlian Li, Ashworth & Witkowski 18,41 Plagiogramma minus var. nanum (Gregory) Chunlian Li, Ashworth & Witkowski 41,45 Plagiogramma pulchellum var. pygmaeum (Greville) H.Peragallo & M.Peragallo 45 Plagiogramma tenuissimum Hustedt 41,45 Plagiotropis lepidoptera (Gregory) Kuntze 37,41 Plagiotropis lepidoptera var. minor (Cleve) Czarnecki & J.L.Wee 41 Plagiotropis lepidoptera var. proboscidea (Cleve) Reimer 41 Planothidium depertidum (Giffen) Witkowski, Lange-Bertalot & Metzeltin 40,41 Planothidium hauckianum (Grunow) Bukhtiyarova 18,38 Planothidium hauckianum var. rostratum (Schulz ex Hustedt) Andresen, Stoermer & 25 Kreis, Jr. Planothidium lanceolatum (Brébisson ex Kützing) Lange-Bertalot 25 Planothidium lilljeborgei (Grunow) Witkowsi, Lange-Bertalot & Metzeltin 45 Planothidium rostratoholoarcticum Lange-Bertalot & Bąk 25

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Pleurosigma aestuarii (Brébisson ex Kützing) W.Smith 37 Pleurosigma angulatum (Quekett) Smith 5,6,8,12,51 Pleurosigma delicatulum Smith 6,48 Pleurosigma elongatum Smith 6,7,15,17,25,29,37,38,44,48 Pleurosigma formosum Smith 6,41 Pleurosigma formosum var. dalmatica (dalmaticum) Grunow 18 Pleurosigma normani Ralfs 3,6,7,9,15,17,18,21,29,31,33,36,41,48,50,51,56 Pleurosigma rigidum Smith 6,18,48 Pleurosigma salinarum (Grunow) Grunow 5,12,18,25,28,51 Pleurosigma strigosum Smith 3,44 Podocystis perrinensis Ricard 6,17,29 Proschkinia bulnheimii (Grunow) Karayeva 45 Proschkinia complanata (Grunow) D.G.Mann 41 Psammodictyon panduriforme (W.Gregory) D.G.Mann 5,6,12,18,28,37,48,51 Psammodictyon panduriforme var. continuum (Grunow) Snoeijs 45 Psammodictyon rudum (Cholnoky) D.G.Mann 41 Psammodiscus nitidus (Gregory) Round & Mann 18,28,48 Pseudo-nitzschia calliantha Lundholm, Moestrup & Hasle 48,49,51,52 Pseudonitzschia delicatissima (Cleve) Heiden 6,8,11,31,48,50,51,56 Pseudo-nitzschia fraudulenta (Cleve) Hasle 6,11,48,50,51 Pseudo-nitzschia pseudodelicatissima (Hasle) Hasle 6,8,9,29,31,48,51,55 Pseudo-nitzschia pungens (Grunow ex Cleve) Hasle 3,6,8,9,11,31,46,47,48,50,51,52,56 Pseudo-nitzschia pungens var. aveirensis Lundholm, Churro, Carreira & Calado 49 Pseudo-nitzschia seriata (Cleve) H.Peragallo 11,48,51 Pseudostaurosira elliptica (Schumann) Edlund, Morales & Spaulding 44 Pseudostaurosira perminuta (Grunow) Sabbe & Wyverman 41 Pteroncola inane (Giffen) Round 5 Rhabdonema adriaticum Kützing 5,6,8,15,18,28,29,36,48 Rhabdonema arcuatum (Lyngbye) Kützing 48 Rhabdonema minutum Kützing 37 Rhaphoneis amphiceros f. gemmifera (Ehrenberg) Peragallo & Peragallo 18 Rhoicosphenia abbreviata (Agardh) Lange-Bertalot 20,27,37 Rhoicosphenia marina (Kützing) Schmidt 5 Rhopalodia acuminata Krammer 44 Rhopalodia constricta (W.Smith) Krammer 18 Rhopalodia gibberula (Ehrenberg) Müller 20 Rhopalodia musculus (Kützing) Müller 17,18,28 Scoliopleura peisonis Grunow 28 Sellaphora pupula (Kützing) Mereschkowsky 20,32,51 Seminavis basilica Dainelidis 41 Seminavis eulensteinii (Grunow) D.B.Danielidis, K.Ford & D.Kennett 18 Seminavis insignis A.Blanco & S.Blanco 40,41 Seminavis robusta Danielidis & Mann 23,41,48 Seminavis strigosa (Hustedt) Danielidis & Economou-Amilli 40,44 Simonsenia delognei (Grunow) Lange-Bertalot 20 Stauroneis anceps Ehrenberg 20 Stauroneis membranacea (Cleve) Hustedt 5 Stauroneis smithii Grunow 22 Staurophora amphioxys (Gregory) Mann 18,28 Staurosirella martyi (Héribaud-Joseph) E.A.Morales & K.M.Manoylov 37 Staurosirella pinnata (Ehrenberg) D.M.Williams & Round 38 Stenopterobia sigmatella (Gregory) Ross 6 Striatella delicatula Kützing Grunow ex Van Heurck 6,8,48,56

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Striatella unipunctata (Lyngbye) Agardh 5,6,7,8,9,11,15,17,18,29,31,32,36,37,41,48,50, 51,52 Surirella angusta Kützing 20,37 Surirella brebissonii Krammer & Lange-Bertalot 22 Surirella elegans Ehrenberg 17,37 Surirella fastuosa (Ehrenberg) Ehrenberg 3,6,7,17,18,29,48 Surirella minuta Brébisson 25,37 Surirella muelleri Hustedt 37 Surirella ovalis Brébisson 14,20,27,37 Surirella pandura Peragallo & Peragallo 6,48 Surirella robusta Ehrenberg 3 Surirella striatula Turpin 3,4,6,17,18,20,25,48 Synedra fulgens (Greville) Smith 6 Synedra gaillonii var. macilenta (Grunow) H.Peragallo 18,23 Tabellaria flocculosa (Roth) Kützing 6 Tabularia affinis var. acuminata (Grunow) Aboal 25 Tabularia fasciculata (Agardh) Williams & Round 5,12,18,25,28,37,44,51 Tabularia investiens (W.Smith) Williams & Round 37,41 Tabularia parva (Kützing) D.M.Williams & Round 5,12,18,44,51 Tabularia tabulata (C.Agardh) Snoeijs 6,25,32,44 Tetramphora intermedia (Cleve) Stepanek & Kociolek 18 Tetramphora lineolata (Ehrenberg) Mereschkowsky 41 Tetramphora rhombica (Kitton) Stepanek & Kociolek 6,48 Tetramphora sulcata (Brébisson) Stepanek & Kociolek 41 Tetramphora ostrearia (Brébisson) Mereschkowsky 45 Thalassionema fraunfeldii (Grunow) Hallegraeff 3,6,7,8,15,17,21,26,29,31,36,48,50,51,52 Thalassionema nitzschioides (Grunow) Mereschkowsky 3,6,7,8,9,11,21,29,31,36,37,48,50,51,52,55,56 Thalassiophysa hyalina (Greville) Paddock & P.A.Sims 7,29,48 Thalassiothrix longissima Cleve & Grunow 3,6,8,26,29,48,50,51 Thalassiothrix mediterranea Pavillard 6,7,8,15,29,31,36,37,48,50 Toxonidea insignis Donkin 5,12,18,51 Trachyneis aspera (Ehrenberg) Cleve 13,18,41,48 Trachysphenia acuminata Peragallo 45 Trachysphenia australis Petit 18,28,48 Trachysphenia australis var. rostellata Hustedt 23 Tryblionella acuminata Smith 18,20,28 Tryblionella angustata W.Smith 22,25 Tryblionella apiculata Gregory 5,12,18,27,28,41,44,51 Tryblionella circumsuta (Bailey) Ralfs 48 Tryblionella coarctata (Grunow) Mann 4,28,41 Tryblionella compressa (Bailey) Poulin 24,28 Tryblionella granulata (Grunow) Mann 18,44 Tryblionella hungarica (Grunow) Frenguelli 25 Tryblionella levidensis W.Smith 22 Tryblionella marginulata (Grunow) Mann 45 Tryblionella navicularis (Brébisson) Ralfs 18 Tryblionella pararostrata (Lange-Bertalot) Clavero & Hernández-Mariné 44 Tryblionella punctata Smith 18 Tryblionella victoriae Grunow 38 Ulnaria acus (Kützing) Aboal 22 Ulnaria danica (Kützing) Compère & Bukhtiyarova 14,37 Ulnaria ulna (Nitzsch) Compère 6,7,15,17,20,27,29,34,38,56

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References REVISIONS Reference System is APA 6th Edition When submitting a revised version of a paper, the author must submit a detailed “Response to the reviewers” that states point In-text Citation with APA by point how each issue raised by the reviewers has been cov- The APA style calls for three kinds of information to be included in in- ered and where it can be found (each reviewer’s comment, fol- text citations. The author's last name and the work's date of publica- lowed by the author’s reply and line numbers where the tion must always appear, and these items must match exactly the cor- changes have been made) as well as an annotated copy of the responding entry in the references list. The third kind of information, main document. Revised manuscripts must be submitted the page number, appears only in a citation to a direct quotation. within 15 days from the date of the decision letter. If the revised version of the manuscript is not submitted within the al- ....(Crockatt, 1995). located time, the revision option may be cancelled. If the sub- Direct quote from the text mitting author(s) believe that additional time is required, they should request this extension before the initial 15-day period "The potentially contradictory nature of Moscow's priorities sur- is over. faced first in its policies towards East Germany and Yugoslavia," (Crockatt, 1995, p. 1). Accepted manuscripts are copy-edited for grammar, punctua- tion, and format. Once the publication process of a man- Major Citations for a Reference List in Table 2. uscript is completed, it is published online on the journal’s Note: All second and third lines in the APA Bibliography should be in- webpage as an ahead-of-print publication before it is included dented. in its scheduled issue. A PDF proof of the accepted manuscript is sent to the corresponding author and their publication approval is requested within 2 days of their receipt of the proof.

Table 2. Major Citations for a Reference List Material Type Reference List/Bibliography A book in print Baxter, C. (1997). Race equality in health care and education. Philadelphia: Ballière Tindall, p. 110-115, ISBN 4546465465 A book chapter, print version Haybron, D.M. (2008). Philosophy and the science of subjective well-being. In M. Eid & R. J. Larsen (Eds.), The science of subjective well-being (p. 17-43). New York, NY: Guilford Press. ISBN 4546469999 An eBook Millbower, L. (2003). Show biz training: Fun and effective business training techniques from the worlds of stage, screen, and song. p. 92-90. Retrieved from http://www.amacombooks.org/ (accessed 10.10.15) An article in a print journal Carter, S., Dunbar-Odom, D. (2009). The converging literacies center: An integrated model for writing programs. Kairos: A Journal of Rhetoric, Technology, and Pedagogy, 14(1), 38-48. Preview article in a journal Gaudio, J.L., Snowdon, C.T. (2008). Spatial cues more salient than color cues in cotton-top tamarins (Saguinus with DOI oedipus) reversal learning. Journal of Comparative Psychology, https://doi.org/10.1037/0735-7036.122.4.441 Websites - professional or The World Famous Hot Dog Site. (1999, July 7). Retrieved January 5, 2008, personal sites from http://www.xroads.com/~tcs/hotdog/hotdog.html (accessed 10.10.2015) Websites - online government U.S. Department of Justice. (2006, September 10). Trends in violent victimization by age, 1973-2005. Retrieved publications from http://www.ojp.usdoj.gov/bjs/glance/vage.htm (accessed 10.10.2015) Photograph (from book, mag- Close, C. (2002). Ronald. [photograph]. Museum of Modern Art, New York, NY. Retrieved azine or webpage) from http://www.moma.org/collection/object.php?object_id=108890 (accessed 10.10.2015) Artwork - from library data- Clark, L. (c.a. 1960's). Man with Baby. [photograph]. George Eastman House, Rochester, NY. Retrieved from base ARTstor Artwork - from website Close, C. (2002). Ronald. [photograph]. Museum of Modern Art, New York. Retrieved from http://www.moma.org/collection/browse_results.php?object_id=108890 (accessed 10.10.2015)